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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.
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International Review of Sport and Exercise Psychology
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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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Published online: 23 Jun 2020.
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The eects 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 eects of
mental practice on performance, leaving it open whether imagery
can also enhance outcomes other than performance such as
motivational or aective outcomes. We performed a meta-analysis
to extend the current understanding of the eectiveness of
imagery in sports on any sport specic outcome and the
relevance of additional variables potentially moderating the eect.
The overall eect of imagery interventions was medium in
magnitude with d= 0.431 (95% CI [0.298, 0.563]). Imagery
interventions signicantly enhanced motor performance,
motivational outcomes, and aective outcomes. Summarized
across all outcomes, imagery combined with physical practice was
more eective than physical practice alone, indicating dierential
eects of imagery and physical practice. We found the same
pattern of result for performance outcomes. The eectiveness 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-aective 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. Dierent to mental practice,
© 2020 Informa UK Limited, trading as Taylor & Francis Group
CONTACT Bianca A. Simonsmeier
Supplemental data for this article can be accessed at
imagery is a specic 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 eectiveness of imagery interventions by investigating the eects of
dierent 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 eec-
tiveness of mental practice and indicated positive eects 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 eectiveness 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 rst evidence
on the eectiveness of mental practice on performance, conclusions about the eective-
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 eect of
mental practice on performance when compared to no-treatment control conditions
with d= 0.527 comprising 62 eect 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 eect sizes from the research of the past 25 years. They also found a posi-
tive eect comparable in magnitude of d= 0.419 which was, however, substantially lower
when accounting for publication bias (d= 0.264). Besides demonstrating the eectiveness
of mental practice to enhance performance, the two meta-analyses provide further valu-
able insights into relevant variables moderating the eect 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
eectiveness 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 dier (Murphy & Martin, 2002), a meta-analysis on the eects
of imagery specically is still outstanding. The present analysis aims at extending results
of previous meta-analyses in three ways: by implementing dierent 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 eectiveness of mental prac-
tice to enhance performance. It is however suggested that imagery is eective to enhance
a variety of outcomes such as psychological skills and not only performance as indicated in
dierent 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
Table 1. Characteristics of the previous four meta-analyses on mental practice.
search word
Explicit inclusion and
exclusion criteria
Accounting for
dependency of
eect sizes
Tests for
publication bias
Included control
types of
outcomes n(k)
[95% CI]
Feltz and
N/A 1934
.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
eect size
published vs.
.Simple control
.Motivational control
(no practice control
group with same
number of
Performance 60 (146) .48 (.67) .Task type
N/A 1949
.One condition mental
practice alone (mental/
physical practice group
combined excluded)
.Adequate control
.Provide the necessary
no no N/A .Direct
.Motivation (perform
unrelated tasks in
Performance 21 (44) .68 (.11) .Type of
.Number of
et al.
mental practice1934
.Reported (or allowed
the retrieval of) tests of
performance under a
mental practice
condition in
comparison with a no-
treatment control
no no .Fail safe N .No-contact control
group (e.g. wait-list)
.Equivalent control
group (e.g. non-
treatment activity)
Post-post Performance 35 (62) .527 .Duration of
Toth et al.
mental practice
OR imagery
.Compare the
performance of
participant engaging
in mental practice with
no no .Fail-safe N
.Trim and ll
.Cognitively active
(e.g. mental
.Cognitively passive
(e.g. reading)
Performance 37 (99) 0.419
.Duration of
.Type of task
Table 1. Continued.
search word
Explicit inclusion and
exclusion criteria
Accounting for
dependency of
eect sizes
Tests for
publication bias
Included control
types of
outcomes n(k)
[95% CI]
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
.Minimal cognitive
control (e.g. quiet
.Type of
the eectieness of imagery on other outcomes such as anxiety or self-condence (e.g.
Callow et al., 2001; Hale & Whitehouse, 1998; Hammond et al., 2012). It is desriable to evalu-
ate the eectiveness of imagery on outcomes other than performance (Wakeeld & Smith,
2012) to obtain an overall picture of the eectiveness of imagery interventions in sport. As
the previous meta-analyses did not consider other outcomes than performance, the eect
of imagery on other outcomes is still unclear. To estimate the overall eectiveness of
imagery, we included studies independent of the outcome assessed in the present
meta-analysis. In our classication 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 aective and motivational outcomes, rehabilitation outcomes,
and psychological skills.
Second, imagery has emerged as a distinct research eld within the domain of sport
psychology and has signicantly 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 dier-
ences in the imagery content, ve major types have been proposed (Hall et al., 1998;
Paivio, 1985). These are (1) cognitive specic (CS; i.e. images of skills), (2) cognitive
general (CG; i.e. images of strategies), (3) motivational specic (MS, i.e. images of goals),
(4) motivational general-arousal (MG-A, i.e. images of arousal and aect), and (5) motiva-
tional general-mastery (MG-M, i.e. imagery of cognitions including self-condence 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 eectiveness, respectively.
Third, previous meta-analyses demonstrated the eectiveness of mental practice com-
pared to active and passive control groups without considering dierences 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 eld 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 specically, 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 ndings of the
previous meta-analyses and to estimate the eectiveness of imagery compared to
dierent control groups, the current meta-analysis included any kind of control group
and systematically investigated variations in the eectiveness of imagery interventions.
Fourth, previous meta-analyses used dierent types of comparisons to determine the
eects of mental practice potentially leading to dierent magnitudes in eect sizes.
While the previous meta-analyses included both, prepost and post-post comparisons
(Feltz & Landers, 1983; Hinshaw, 1991), or post-post comparisons only (Driskell et al.,
1994), the most recent meta-analysis used prepost gains to operalize the performance
change due to the mental practice (Toth et al., 2020). Until now, no systematic analysis inves-
tigating dierences in the magnitude of eect 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 eects 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 ndings. 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 eect sizes per study. This is proble-
matic as ignoring covariance at the study level can result in biased standard errors and
condence 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 eect 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 eld of sport psychol-
ogy and is widely accepted in practical settings to enhance performance. Despite the con-
tribution of previous meta-analyses on the eectiveness of mental practice on
performance, the quantitative summary of the existing empirical evidence on the
eects of dierent types of imagery interventions and the eect on various outcomes
in sports is still outstanding. Further, eects of methodical aspects, for example using
dierent control groups and types of comparisons to determine the eectiveness of
imagery, are not well understood yet. The present study aims to add to previous meta-ana-
lyses and to ll this gap in the literature on imagery interventions in sports.
We a-priori formulated the following ve research questions and hypotheses:
1. Is imagery eective to enhance sport related outcomes and is the eect causal? We
expect to nd a positive and causal eect of imagery on sports related outcomes
(Hypothesis 1).
2. Is imagery eective when compared to a passive and an active control condition?
Moreover, is physical practice combined with imagery more eective than physical
practice alone? We assume that the overall eect of imagery interventions compared
to dierent control conditions is positive (Hypothesis 2a) and that physical practice
combined with imagery is more eective than physical practice alone (Hypothesis 2b).
3. Does the magnitude of the eect of imagery vary due to dierent comparisons
employed? We expect to nd a higher eect for prepost comparisons compared to
eects for post-post and prepost gains comparisons (Hypothesis 3).
4. Is imagery eective to enhance performance and other sport specic outcomes? We
assume an eectiveness of imagery on various outcomes (Hypothesis 4) (Guillot &
Collet, 2008; Martin et al., 1999).
5. Are dierent types of imagery (equally) eective? We assume to nd positive eects for
all dierent types of imagery and to obtain no dierences between them in their eec-
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 identied 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 identied 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 ow 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 eects of an imagery intervention. The eect 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
studies/eect sizes comparing one imagery intervention to another imagery intervention
or eect sizes where the treatment group diered 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.
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 specic. (3) The eects 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 ndings (i.e. not a re-analysis of already reported
ndings or a review) to avoid double coding of eect sizes.
Coding of studies occurred in two steps. First, all abstracts were screened by the rst
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 classied 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 rst and third authors coded half of the full texts,
respectively. Overall, 55 studies were identied 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 eect 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 eect 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.
Data coding
We coded all eect sizes reported in the included studies and did not limit the number of
eects 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 eect sizes whenever possible and com-
puted a standardized eect size the same way for each study, as described in the Sup-
plemental Materials. For each included eect, we coded the values of the moderators.
Preparation of eect sizes
For each eect, we computed the eect size Cohensdfrom the coded raw data using
syntax (for more details, see the Supplemental Materials). For 61 eect sizes, raw data
was not available. Instead, we included the reported Cohensdvalues or the transformed
-values, t-values, or F-values. We analyzed three dierent types of comparisons (pre
post, post-post, and prepost gains comparisons) to estimate the overall eectiveness
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 eect 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
Hedgesginstead of Cohensd. The alternative approaches did not meaningfully
change the overall eect sizes and moderating eects.
Statistical analysis
Before aggregation of data from single studies, we identied outliers using specic outlier
diagnostics for meta-analysis (Viechtbauer & Cheung, 2010). Based on the examination of
studentized deleted residuals, DFFITS values, Cooks distances, and COVRATIO values (for
more details see Viechtbauer & Cheung, 2010), we removed two eect sizes out of one
study (Afrouzeh et al., 2015).
Most of the included studies provided multiple eect sizes for the eects of an imagery
intervention. Consequently, eect 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 eects statistical models were used
for all analysis (Raudenbush, 2009), to address the presumed heterogeneity of eects.
First, we estimated a simple RVE meta-regression model to estimate the overall eect of
imagery interventions. Second, to estimate the variability in the eect size due to modera-
tor variables, we estimated a mixed-eects 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 signi-
cant results to be published which can in turn bias the overall eect 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-ll analyses (Duval &
Tweedie, 2000) estimating the number of missing studies that might exist and the
eect that these studies might have had on the overall meta-analytic eect.
Study characteristics
A total of 55 studies reporting 401 eect sizes obtained with 1438 participants were
included in the nal 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 eect sizes were from randomized controlled trials (62%), followed by controlled
trials (26%), and prepost comparisons (12%). Studies included outcomes of motor learn-
ing and performance (77%), psychological skills (11%), motivational outcomes (8%),
aective outcomes (3%), and strategies and problem solving (2%).
Overall eectiveness of imagery interventions
Hypothesis 1
Table 2 summarizes all results of the meta-analysis. The meta-analytically obtained overall
eect size based on 401 eect sizes from 55 studies indicated a positive, medium, and
statistically signicant eect of imagery with Cohensd= 0.431, 95% CI [0.298, 0.563]. The
eect was also signicantly positive for randomized controlled trials, indicating a causal
eect of imagery with d= 0.254 (95% CI [0.179, 0.530]). The eects of imagery were
evident in both post-tests and retention tests, indicating lasting changes due to the
Hypothesis 2
The eectiveness of imagery was signicantly 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 eective 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 eects of imagery were comparable to the
eects of physical practice (d= 0.125, 95% CI [0.175, 0.431]). Moderation analyses
did not indicate any dierences across the dierent control conditions with F(7.38) =
0.404, p= .755.
Contributing Factors to the eectiveness of imagery interventions
Hypothesis 3
Regarding hypothesis 3, imagery was eective 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 aective outcomes (d= 0.269, 95% CI [0.001, 0.537)]. There were no signi-
cant dierences in the magnitude of the eect depending on the dierent outcomes (F
(5.89) = 1.32, p= .353). Thus, the results provide evidence for our third hypothesis, indi-
cating the eectiveness of imagery interventions for performance but also psychological
Hypothesis 4
The eectiveness of imagery interventions varied due to the employed comparison (F
(16.90) = 7.53, p= .005). The eect was largest for prepost 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 prepost 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 eect sizes,
results were comparable with the largest eect for prepost 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 prepost gains (d= 0.232, 95% CI [0.097, 0.368)]. In summary, eect sizes sig-
nicantly vary in magnitude due to the employed comparison, as expected in our fourth
Hypothesis 5
Few studies reported their employed imagery type, leading to insucient power to deter-
mine eect 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 specic imagery was eective to enhance sport
Table 2. Number of studies (j), Number of eect sizes (k), Eect size (d), 95% Condence interval,
measure of heterogeneity τ
, and signicance of the moderator analyses.
Coding Options j k d 95% CI τ
Sign. moderator
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
Comparison **
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 –– –
Aective 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 ––
Sports ns
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 ––
Introduction ns
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 ––
Setting ns
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
specic 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 fth hypothesis.
Exploratory moderators
Of all included moderators, the only signicant moderator was the number of sessions of
the imagery training. The eectiveness was signicantly higher the more sessions the
implementation included (F(18) = 11, p= .004). None of the other moderators reached sig-
nicance, demonstrating a robust eect of imagery across dierent age groups, imagery
specics, and settings.
Checks for publication bias
Visual inspection of the funnel plot (see Figure 2) for the study level (i.e. the average eect
size of each study) and eect size level (i.e. all 401 eect sizes) and Egger regressions for
random eects (Egger et al., 1997) did not indicate signicant asymmetry on study level
Table 2. Continued.
Coding Options j k d 95% CI τ
Sign. moderator
Script ns
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
Perspective ns
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
Athlete characteristics
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: : insucient number of data points for the analysis; ref: reference category; ns: not signicant, *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.
and eect size level. Trim and ll (Duval & Tweedie, 2000) did not indicate any missing
studies, keeping the results of the meta-analysis unchanged. The results suggest that
our ndings are unlikely distorted by publication bias.
Eectiveness of imagery interventions
The main goal of the meta-analysis was to extend previous meta-analyses on mental prac-
tice by examining the overall eects of imagery on sport specic outcomes, its generaliz-
ability, and identifying relevant moderating variables. We summarize the results of the
meta-analysis in ve key ndings. First, imagery is eective to enhance not only perform-
ance but also other sport specic outcomes. Second, imagery signicantly enhances the
eects of physical practice. Third, the magnitude of eect sizes vary across dierent
types of comparisons. Fourth, imagery eects are dosage specic. Fifth, there still exist
many gaps in the literature on imagery. While the dierent 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 eect size Cohenss d for the eect size
level (left) and the study level (right).
Key nding 1
As expected, imagery was eective to enhance sport specic outcomes with an overall
eect size of d= 0.431. The obtained eect size summarizing various sport specic out-
comes is comparable to previous meta-analyses on mental practice focusing on perform-
ance outcomes, which found eect sizes of d= 0.527 (Driskell et al., 1994) and d= 0.419
(Toth et al., 2020). It is also comparable to the eects from other meta-analyses investi-
gating eects of psychological interventions on sports performance, such as goal
setting (Kyllo & Landers, 1995) or self-talk interventions (Hatzigeorgiadis et al., 2011).
The eect of imagery is causal rather than correlation, as the eect was still present in
randomized controlled trials holding third variables constant. The imagery was signi-
cantly more eective compared to a passive control group and an active control group.
Results suggest a long-term eect as the eectiveness was demonstrated in retention
tests. It was further evident across a variety of dierent participant, intervention, and
outcome characteristics, indicating a robust eect of imagery across dierent settings.
Key nding 2
Imagery combined with physical practice was more eective than physical practice alone,
which follows the assumption that imagery enhances the eects 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 dierential inuences 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 eectiveness of studies with equal practice trials
(e.g. imagery plus physical practice vs. physical practice plus a ller task), the eect of
imagery was still positive and signicant, both on motor tasks and other tasks. Therefore,
the results of the current meta-analysis also indicate dierential inuences of imagery and
physical practice. Furthermore, the dierential eects are likely to be found for both motor
performance and other sport specic outcomes such as psychological outcomes.
Key nding 3
We demonstrate that the magnitude of eect size for imagery interventions diers due to
the type of comparison. Our results highlight the relevance to account for dierent com-
parisons, as prepost eects signicantly dier from post-post eects and prepost gains.
The last comparison is most appropriate for intervention studies that focus on learning or
improvement in specic 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 specic 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 eect 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
assumptions and that gain scores can have acceptable validities and reliabilities under
more realistic assumptions (Maris, 1998; May & Hittner, 2010; Zimmermann & Williams,
Key nding 4
Eects of imagery are dosage specic. Our results suggest that the more sessions
employed, the more eective the imagery intervention. This result supports the results
from previous meta-analyses and reviews, also indicating dosage speciceects 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 eective the more sessions employed, our ndings provide evidence for the poten-
tial of imagery as one form of deliberate practice. However, the interventions of the single
studies were designed to nd positive and high eects 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 eects.
Key nding 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 eect remains to be determined. On a descrip-
tive level, we found great dierences in the magnitude of eect size regarding, for
example, imagery type, the participantsimagery ability or skill level, the employed per-
spective, or temporal equivalence of the imagery. However, we were not able to test
these dierences 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 dierences
in the implementation. In turn, it needs a great amount of studies to test dierences in
the eectiveness caused by the specics of imagery and implementation systematically.
To understand the impact of characteristics of the participants, the specics 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, specics of imagery greatly varied across studies, resulting in few studies
within each moderator category. To fully understand the eectiveness of imagery and
under which condition imagery is most eective, 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 eects of imagery other than cognitive
specic imagery (e.g. Martin et al., 1999; Munroe-Chandler et al., 2012)ordierences in
the eectiveness 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 eects 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 aective outcomes (e.g. Mellalieu et al., 2009; Ramsey et al.,
2010). Future research may extend the understanding of the eectiveness of imagery
by investigating eects 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 specic 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 eect
sizes that could be included in moderator analyses as compared to the amount of eect
sizes included in the general analysis.
Generalizability of the ndings and conclusion
The medium positive eect of imagery in sport specic outcomes reported in the present
meta-analysis can be interpreted as non-confounded eects of imagery, as studies were
only included when the intervention and control condition only diered 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 eect of imagery was
still signicant for randomized controlled trials, possible inuences of third variables can be
ruled out. The eects were robust as compared to passive control groups and active control
groups implementing another intervention. Further, eects 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 eect sizes, and had
sucient coding reliability to increase the validity of our ndings.
Due to the great variety in the implementation of imagery interventions, some modera-
tors were underrepresented. For example, there is little evidence on the eects of imagery
for participants with low imagery ability, professional athletes, or participants with imagery
experience. Similarly, only a few studies investigated the eects of imagery types other
than cognitive specic imagery. Furthermore, some specic 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.
Overall, imagery was conrmed to be an eective strategy for enhancing various out-
comes in sports. Furthermore, we identied moderators that could further explain the
eects of imagery, enhance our knowledge regarding the eectiveness of imagery inter-
ventions, and provide directions for future research. The medium eect 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 prepost 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.
Disclosure statement
No potential conict of interest was reported by the author(s).
Bianca A. Simonsmeier
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... Motor imagery is established in the applied field of sport psychology and its importance and effectiveness in terms of influencing performance and rehabilitation processes has been extensively documented (for reviews, see Di Rienzo et al., 2014;Simonsmeier et al., 2020). The efficiency of MI relies on neurofunctional equivalence which illustrates the neuronal activation similitude during mental and real practice. ...
... Alternatively, extraversion is comprised of different facets: assertiveness, positive emotionality, and sociability. Imagery, when performed in a motivational context, is often used to create positive emotions and confidence (Simonsmeier et al., 2020), so in turn a tendency for positive emotions and assertiveness could be beneficial to the imagery process. Encouraging imagery, in general, could lead to improve imagery skills, irrespective of the imagery function. ...
... Looking ahead, it will be necessary to investigate in more depth what this link is based on. Classifying the wide individual differences in MI ability beyond states will be a challenging task ahead (McAvinue & Robertson, 2008), and tackle the lack of an understanding of why certain people are better than others at such an important skill (Simonsmeier et al., 2020). Earlier conceptualisation about imagery (Cumming & Williams, 2013;McDougall & Pfeifer, 2012;Morris et al., 2005) may be reconsidered to benefit of refining the individual factors (see theoretical concept, Appendix C). ...
Motor imagery (MI) training is used to improve motor performance in both patients and athletes. The putative link between personality and MI remains however largely underexplored. In this pilot study, 72 sports students performed MI and physical execution of a finger pointing task. MI ability was assessed through the mental chronometry paradigm that captured the temporal components of imagery, as well as self-report measures of imagery vividness and imagery ease. Personality dimensions were assessed with the five-factor model. Extraversion was found to be significantly correlated with MI ability as measured with mental chronometry ( r = .37, p = .001) but not with imagery vividness ( r = −.08, p = .481) or imagery ease ( r = −.04, p = .741). The other personality dimensions were unrelated to MI ability (all p > .05). Based on these findings, we postulate that extravert individuals may have an advantage in controlling and maintaining the temporal aspect of mental movements. This may help extraverts to better benefit from imagery training.
... Motor learning is often defined as a relatively permanent change in skill performance due to physical practice of a movement [1], research, however, highlights that cognitive training techniques, such as mental imagery, can also facilitate motor learning when combined with physical practice or alone [2][3][4]. Mental imagery refers to the ability to simulate perceptual and motor information in our mind without sensorimotor input [5]. Under the broad category of mental imagery is motor imagery (MI), which focuses specifically on the cognitive recreation of a movement without overt motor execution [6]. ...
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Cognitive training techniques such as motor imagery (MI)-cognitive simulation of movement , has been found to successfully facilitate skill acquisition. The MI literature emphasizes the need to accurately imitate key elements of motor execution to facilitate improved performance outcomes. However, there is a scarcity of MI research investigating how contemporary approaches to motor learning, such as nonlinear pedagogy (NLP), can be integrated into MI practice. Grounded in an ecological dynamics approach to human movement, NLP proposes that skilled action is an emergent process that results from continuous interactions between perceptual information of the environment and movement. This emergent process can be facilitated by the manipulation of key task constraints that aim to encourage learners to explore movement solutions that satisfy individual constraints (e.g., height and weight) and achieve successful performance outcomes. The aim of the present study was to explore the application of a NLP approach to MI approach for skill acquisition. Fourteen weightlifting beginners (two female and 12 male) participated in a 4-week intervention involving either NLP (i.e. analogy-based instructions and manipulation of task constraints) or a linear pedagogy (LP; prescriptive instructions of optimal technique, repetition of same movement form) to learn a complex weightlifting derivative. Performance accuracy, movement criterion (bar-bell trajectory type), kinematic data, and quantity of exploration/exploitation were measured pre-mid-post intervention. No significant differences (p = .438) were observed in the amount of exploration between LP (EER = 0.41) and NLP (EER = 0.26) conditions. Equivalent changes in rearward displacement (R×D) were observed with no significant differences between conditions for technique assessments 1, 2, or 3 (p = .13-.67). Both NLP and LP conditions were found to primarily demonstrate 'sub-optimal' type 3 barbell trajectories (NLP = 72%; LP = 54%). These results suggest that MI instructions prescribing a specific movement form (i.e., LP condition) are ineffective in restricting available movements to a prescribed technique but rather the inherent task constraints appear to 'force' learners to explore alternative movement solutions to achieve successful performance outcomes. PLOS ONE PLOS ONE | Citation: Lindsay RS, Komar J, Chow JY, Larkin P, Spittle M (2023) Different pedagogical approaches to motor imagery both demonstrate individualized movement patterns to achieve improved performance outcomes when learning a complex motor skill. PLoS ONE 18(11): e0282647. https://
... The results obtained in this experiment also show that the players who used MI improved their selfe cacy score, leading to their success in ball launcher task, which validates our second hypothesis. The results of this study con rm those of previous research studies, which show that MI also has a motivational function (Hall et al., 1992;Hardy, 1998;Simonsmeier et al., 2020) and can be used by tennis players and coaches to improve self-con dence and feelings of competence or self-e cacy (Crespo & Reid, 2007;Robin & Dominique, 2022;Weinberg & Jackson, 1990). Since self-e cacy is known to be a powerful "predictor" of sports performance (Feltz et al., 2008), any intervention allowing it to be increased will be useful for coaches and bene cial for players (Weinberg & Jackson, 1990). ...
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The aim of this original study was to evaluate the effects of positive motor imagery (MI: imagining the success of a forehand or backhand shot) according to an internal visual modality centred on the movement and the target to be reached on tennis performance. 24 young non-expert players were randomly divided into two groups: control and MI, and performed 3 experimental phases. The first (pre-test) consisted of performing 6 blocks of 5 forehand and backhand groundstrokes, sent randomly by a ball launcher, towards the baseline and then a super tie-break. The second phase consisted of 12 acquisition sessions, each including, after a standardized warm-up, 15 minutes of background rally in pairs. The participants of the MI group were instructed, after unprovoked errors on their part, to imagine performing the previous shot correctly. The last phase (post-test) was identical to the pre-test. The efficiency score of shots made and the number of errors committed at the pre- and post-test served as dependent variables. The results of this study indicate that participants in the MI group performed better than the control group at post-test. The MI, performed after errors, has positive effects on the quality of the shot and reduces the number of unforced errors of tennis players. The use of this strategy is discussed and applied recommendations are proposed.
... Indeed, AIP has been shown to improve subsequent action-execution. However, performance improvements are lower than after action-execution practice (AEP, also called 'physical practice') (Ladda, Lebon, & Lotze, 2021;Lindsay, Larkin, Kittel, & Spittle, 2023;Simonsmeier, Androniea, Buecker, & Frank, 2021;Toth, McNeill, Hayes, Moran, & Campbell, 2020). However, the mechanisms behind the acquisition of action representations that lead to performance improvements and which types of actions representations are acquired in AIP have not been fully uncovered Frank, Kraeutner, Rieger, & Boe, 2023;Kraeutner, Cui, Boyd, & Boe, 2022;Rieger et al., 2023). ...
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Action-imagery practice (AIP) is assumed to result in partly different action representations than action-execution practice (AEP). The present study investigated whether focusing on either kinesthetic or visual aspects of a task during practice amplifies or diminishes such differences between AIP and AEP. In ten sessions, four groups, using either AIP or AEP with either kinesthetic or visual focus, practiced a twelve-element sequence in a unimanual serial reaction time task. Tests involved the practice sequence, a mirror sequence, and a different sequence, each performed with the practice and transfer hand. In AIP and AEP, in both hands, reaction times (RTs) were shorter in the practice sequence than in the different sequence, indicating effector-independent visual-spatial sequence representations. Further, RTs were shorter in the practice hand than in the transfer hand in the practice sequence (but not in the different sequence), indicating effector-dependent representations in AEP and AIP. Although the representation types did not differ, learning effects were stronger in AEP than in AIP. Thus, although to a lower extent than in AEP, effector-dependent representations can be acquired using AIP. Contrary to the expectations , the focus manipulation did not have an impact on the acquired representation types. Hence, modality instructions in AIP may not have such a strong impact as commonly assumed, at least in implicit sequence learning.
... MI may provide a potential strategy to provide simulated exposure to movement demands in rehabilitation, providing a safe approach to managing the fear of re-injury concerns of athletes in responding to perceived risky movement context and movement demands (20,21). It is well established that MI is an effective strategy for improving learning and performance (22)(23)(24)(25) and mental health outcomes (26,27). Specific to the negative psychological symptoms experienced during rehabilitation, MI has been found to decrease fear of reinjury and anxiety and increase confidence in motor abilities following injury (9,28). ...
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Returning to sport and exercise following injury requires the athlete to become more confident in the ability to gradually explore the use of the injured area in increasingly complex and challenging ways. Emotional responses, such as fear of re-injury, are a key mental health barrier to a performer’s return to sport and exercise. To navigate such psychological responses, performers need well-developed psychological strategies, like mental imagery (MI), to facilitate a successful return to pre-injury levels of sport and exercise. MI is a well-established strategy for dealing with negative symptoms associated with injury, providing a safe and less intimidating environment to practice movements that may be perceived as risky and otherwise performed within physical training due to the fear of causing further injury. This paper aims to provide sport psychologists with recommendations on how to utilize MI to reduce fear of re-injury during the rehabilitation process to successfully facilitate return to sport and exercise. Specific examples are also outlined and discussed.
... Indeed, its application is so ubiquitous that it could be described as the Swiss Army Knife of performance psychology. There is substantial literature supporting the efficacy of mental imagery and its many related applications, e.g., the learning of motor skills for dart throwing or basketball free throws, rehearsal of game plans in soccer or routines in figure skating, increasing the self-confidence of badminton players, or facilitating the adherence to rehabilitation programs Hall (2001); Martin et al. (1999);Simonsmeier et al. (2020). ...
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Mental imagery practice is widely used to help athletes prepare for competitions, as it can produce motor actions that enhance performance. The goal of imagery training for athletes is to create realistic images in their minds and to familiarize them with certain procedures, environments, and other aspects related to competition. Traditional imagery training methods use still images or videos, and athletes study the pictures or watch the videos in order to mentally rehearse. However, factors such as distractions and low realism can affect the training quality. In this paper, we present a Virtual Reality (VR) solution and a study that explores our hypotheses that H1: high-fidelity VR systems improve mental imagery skills, that H2: the presence of elements such as virtual onlookers or photographers in the VR environment arouse stronger emotional reactions and affect, and that H3: the presence of elements such as onlookers or photographers in the VR environment results in better mental imagery skill improvement. For that purpose, seven elite snow sports athletes were exposed to three training methods, Video, VR-Empty, and VR-Crowded. Our results show that a VR simulation with virtual onlookers (VR-Crowded) can significantly increase heart rate, which can induce increased emotional arousal. The results from validated questionnaires show no significant difference for the three training methods in terms of mental imagery and affect, but the results show an ascending trend for the athlete’s arousal from Video to the VR-Crowded condition. Gaze detection heat maps of interest areas for the two VR conditions support hypothesis H2 that environmental factors such as the presence of photographers, staff, and onlookers can increase head and eye movement, possibly indicating an increase in emotional arousal during imagery training. According to verbal feedback and interviews, athletes are more likely to use innovative training methods (e.g., the high-fidelity VR method) than traditional video-training methods.
Objectives Imagery training is an effective technique in sport psychology for skill development and enhancement at various levels of skill performance. Despite its application, there is limited evidence to inform decisions around the appropriate doses of imagery duration for performance enhancement of movement in sport and physical activity. The aim of the present study was to experimentally determine whether different imagery durations (8, 13, and 18 min durations in a session) have differential effects on the performance of free-throw shooting (FTS) in the sport of basketball. We applied a dose-response imagery protocol, in which one imagery variable was varied systematically, while other key dose variables were held constant. Methods We recruited 36 male basketball players ( M age =25.17 years SD=4.26) and allocated them to one of three imagery training conditions or a control condition. Participants in the control condition had no imagery training sessions. Imagery repetitions were held constant at 20 repetitions per imagery session with a frequency of 3 imagery sessions per week over four weeks. Results The results showed that the 13- and 18-min imagery durations were more effective than the 8-min duration condition for the basketball free-throw shooting. The 13-min condition was significantly higher at post- and retention-test than at pre-test, indicating it was most effective in this study. Conclusions The findings of the present study highlight the importance of imagery duration in imagery training design and may inform coaches, sport psychologists, and athletes in designing effective programs for individual athletes.
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The VMIQ-2 has been proven a valid and useful psychometric tool to measure the ability of vividness of movement imagery in sports. However, no validity study has been reported in Greek. The purpose of the present study was to examine the validity and reliability of the VMIQ-2 into Greek in adult athletes derived from various sports activities and different athletic levels. The VMIQ-2-GR (n = 160) was examined for translation, construct and discriminant validity, and also for internal consistency and test–retest reliability. CFA did not show acceptable global fit indices and only the index of (x2/df ) showed an acceptable fit. The resulting factors of the EFA highlighted the discrepancy between the Greek version and the original version of the VMIQ-2. The results of the discriminant validity confirmed that the VMIQ-2-GR was well discriminated between subgroups of athletes and, therefore, showed a good discriminant validity. The Cronbach a coefficient was excellent at both measurements (> 0.92 in all cases for all factors). The Spearman rho correlation coefficients were statistically significant (< 0.001) with values > 0.47. The findings of the VMIQ-2–GR suggest that it is a valid and reliable tool and it can be used by sports psychologists, sports physiotherapists, coaches and researchers who aim to apply MI in the Greek athletic population.
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Endurance sports require the sustained maintenance of high effort until the point of task failure. Psychological factors, particularly the perception of effort, exert considerable influence in determining task failure. Training interventions that blend physical and cognitive tasks yielded promising results in enhancing endurance performance. Motor imagery stands out as a method capable of modulating the perception of effort. However, the precise extent to which combining motor imagery and physical training can improve endurance performance remains to be understood. In a pre-post training design, this study aimed to investigate the impact of combining motor imagery with physical training on endurance performance, compared to physical training alone. Two groups of participants were constituted (motor imagery: n = 16; control: n = 17). Both groups performed physical exercises (i.e. isometric wall squat of incremental duration, with 12 training sessions over a period of 14 days), with participants from the motor imagery group also performing motor imagery sessions. Each participant visited the laboratory for experimental procedures twice before and twice after training, during which we assessed endurance performance through a sustained submaximal isometric contraction of the right knee extensors performed until task failure (time to task failure, TTF) at either 20 or 40% of the maximal voluntary contraction. Perceptions of effort and muscle pain were measured regularly during the endurance exercise. We reported no changes in endurance performance for the control group. Endurance performance in the motor imagery group exhibited significant improvements when the intensity of the sustained isometric TTF test closely matched that used in training (i.e. 20% of MVC). However, these enhancements were less pronounced when considering higher exercise intensities (i.e. 40% of MVC). No reduction in perception of effort was observed in both groups. There was a noticeable decrease in muscle pain perception within the motor imagery group following the training. Overall, combining motor imagery and physical training may thus offer a promising avenue for enhancing endurance performance and managing pain in various contexts, from sports to clinical rehabilitation.
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Mental practice is the cognitive rehearsal of a task prior to performance. Although most researchers contend that mental practice is an effective means of enhancing performance, a clear consensus is precluded because (a) mental practice is often defined so loosely as to include almost any type of mental preparation and (b) empirical results are inconclusive. A meta-analysis of the literature on mental practice was conducted to determine the effect of mental practice on performance and to identify conditions under which mental practice is most effective. Results indicated that mental practice has a positive and significant effect on performance, and the effectiveness of mental practice was moderated by the type of task, the retention interval between practice and performance, and the length or duration of the mental practice intervention.
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Measuring student learning is a complicated but necessary task for understanding the effectiveness of instruction and issues of equity in college science, technology, engineering, and mathematics (STEM) courses. Our investigation focused on the implications on claims about student learning that result from choosing between one of two commonly used metrics for analyzing shifts in concept inventories. The metrics are normalized gain (g), which is the most common method used in physics education research and other discipline based education research fields, and Cohen’s d, which is broadly used in education research and many other fields. Data for the analyses came from the Learning About STEM Student Outcomes (LASSO) database and included test scores from 4551 students on physics, chemistry, biology, and math concept inventories from 89 courses at 17 institutions from across the United States. We compared the two metrics across all the concept inventories. The results showed that the two metrics lead to different inferences about student learning and equity due to the finding that g is biased in favor of high pretest populations. We discuss recommendations for the analysis and reporting of findings on student learning data.
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Imagery training with adult athletes is widely used to improve performance. One underlying mechanism is the optimization of mental movement representations. However, past research has focused mainly on adults and has left open whether imagery also improves mental representations and performance in young athletes. The present study examined these questions in a sample of 56 female gymnasts aged 7 to 15 years. In a cross-over experimental design (imagery first vs. imagery last), regular training with imagery was compared to regular training only in high- versus low-expertise athletes. The four-week long imagery training had positive effects on performance only for the high-expertise athletes in the imagery-last condition. The results of the SDA-M method regarding changes in the mental representations were inconsistent. Thus, imagery training can promote motor learning in young athletes only under some conditions. We discuss possible reasons for the heterogeneous results and ways for improving the strength and reliability of the intervention effects.
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Action observation training and motor imagery training have independently been studied and considered as an effective training strategy for improving motor skill learning. However, comparative studies of the two training strategies are relatively few. The purpose of this study was to investigate the effects of action observation training and motor imagery training on the development of mental representation structure and golf putting performance as well as the relation between the changes in mental representation structure and skill performance during the early learning stage. Forty novices were randomly assigned to one of four groups: action observation training, motor imagery training, physical practice and no practice. The mental representation structure and putting performance were measured before and after 3 days of training, then after a 2-day retention period. The results showed that mental representation structure and the accuracy of the putting performance were improved over time through the two types of cognitive training (i.e., action observation training and motor imagery training). In addition, we found a significant positive correlation between changes in mental representation structure and skill performance for the action observation training group only. Taken together, these results suggest that both cognitive adaptations and skill improvement occur through the training of the two simulation states of action, and that perceptual-cognitive changes are associated with the change of skill performance for action observation training.
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Measuring student learning is a complicated but necessary task for understanding the effectiveness of instruction and issues of equity in college STEM courses. Our investigation focused on the implications on claims about student learning that result from choosing between one of two commonly used methods for analyzing shifts in concept inventories. The methods are: Hake's gain (g), which is the most common method used in physics education research and other discipline based education research fields, and Cohen's d, which is broadly used in education research and many other fields. Data for the analyses came from the Learning Assistant Supported Student Outcomes (LASSO) database and included test scores from 4,551 students on physics, chemistry, biology, and math concept inventories from 89 courses at 17 institutions from across the United States. We compared the two methods across all of the concept inventories. The results showed that the two methods led to different inferences about student learning and equity due to g being biased in favor of high pretest populations. Recommendations for the analysis and reporting of findings on student learning data are included.
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Purpose Identifying and understanding causal risk factors for crime over the life-course is a key area of inquiry in developmental criminology. Prospective longitudinal studies provide valuable information about the relationships between risk factors and later criminal offending. Meta-analyses that synthesize findings from these studies can summarize the predictive strength of different risk factors for crime, and offer unique opportunities for examining the developmental variability of risk factors. Complex data structures are common in such meta-analyses, whereby primary studies provide multiple (dependent) effect sizes. Methods This paper describes a recent innovative method for handling complex meta-analytic data structures arising due to dependent effect sizes: robust variance estimation (RVE). We first present a brief overview of the RVE method, describing the underlying models and estimation procedures and their applicability to meta-analyses of research in developmental criminology. We then present a tutorial on implementing these methods in the R statistical environment, using an example meta-analysis on risk factors for adolescent delinquency. Results The tutorial demonstrates how to estimate mean effect sizes and meta-regression models using the RVE method in R, with particular emphasis on exploring developmental variation in risk factors for crime and delinquency. The tutorial also illustrates hypothesis testing for meta-regression coefficients, including tests for overall model fit and incremental hypothesis tests. Conclusions The paper concludes by summarizing the benefits of using the RVE method with complex meta-analytic data structures, highlighting how this method can advance research syntheses in the field of developmental criminology.
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This study attempted to manipulate an athlete's facilitative or debilitative appraisal (direction; Jones, 1995) of competitive anxiety through imagery-based interventions in order to study the effects on subsequent anxiety intensity (heart rate and CSAI-2) and direction (CSAI-2D; Jones & Swain, 1992). In a within-subjects' design, 24 experienced soccer players were relaxed via progressive relaxation audiotape and then randomly underwent an imagery-based video-and audiotaped manipulation of their appraisal of taking a hypothetical game-winning penalty kick under either a "pressure" or "challenge" appraisal emphasis. There was no significant effect for heart rate. A repeated measures MANOVA for CSAI-2 and CSAI-2D scores revealed that for both intensity and direction scores the challenge condition produced less cognitive anxiety, less somatic anxiety, and more self-confidence (all p < .001) than the pressure situation. This finding suggests that a challenge appraisal manipulation taught by applied sport psychologists might benefit athletes' performance.
Objectives Motor imagery (MI) is a dynamic mental state during which the representation of a given motor movement is rehearsed in working memory without overt motor output. Mental practice (MP; also known as motor imagery practice) is the systematic application of MI for the cognitive rehearsal of a task in the absence of overt physical movements. Although MP is known to enhance skilled performance, debate still exists about the magnitude and moderators of these imagery effects. Against this background, and amid concerns about the “reproducibility crisis” in psychology, it seems timely to revisit, update and extend a key meta-analysis of MP effects published over two decades ago – namely, that of Driskell, Copper, and Moran (1994). To this end, the present paper reports a methodological replication of the Driskell et al’s (1994) meta-analysis of MP effects. Design & method Included are 37 studies on MP effects published between 1995 and 2018. Nine factors were selected to examine the extent to which they moderate the effectiveness of mental practice, providing a window into the conditions under which mental practice is most effectively implemented. Practice Type (Mental or Physical), Expertise, Duration of practice (both program and session), Task Type, and Control Type were retained as factors of interest from the original Driskell et al. (1994) meta-analysis. In order to further explore the nuance of mental practice implementation, we additionally examined the Imagery Type, the Performance Measure used, Activity Type (team versus individual activities) and the Setting of the intervention. Results Following publication bias analyses, our results confirm that overall, MP has a small but significant positive effect on performance (r = 0.131). Moderators of this beneficial effect were MP duration, type of task and type of imagery used. Conclusions We conclude that MP has an enduring positive influence on performance.