Flow training, flow states, and performance in elite Athletes

Abstract

Using a single-subject multiple-baseline design, the study examined the efficacy of a flow training program on flow states and performance of four elite level rock-climbers. Having received the intervention that comprised education, goal-setting, self-talk, and mindfulness stages, flow intensity, as measured by the Flow State Scale (FFS-2) increased. In addition, objective performance (time) and self-rated scores improved with, at least, medium effect sizes. Social validation indicated that participants found the training to be rewarding, and in line with the study findings. Such results propose further empirical research on flow training on elite athletes be undertaken to assess the intensity of flow experiences and performance scores. Future research examining retention data and education only interventions are advised. Implications arising from the present data are discussed.

Full text

Flow Training, Flow States, and Performance in Elite
Athletes
CAMERON NORSWORTHY*, RICHARD THELWELL*, NEIL WESTON*,
SUSAN A. JACKSON**
(*) Department of Sport & Exercise Science, Spinnaker Building, Cambridge Road, Portsmouth,
UK University of Portsmouth, UK
(**) PO Box 240, Kenmore, QLD Australia
Using a single-subject multiple-baseline design, the study examined the effi-
cacy of a flow training program on flow states and performance of four elite level
rock-climbers. Having received the intervention that comprised education, goal-set-
ting, self-talk, and mindfulness stages, flow intensity, as measured by the Flow
State Scale (FFS-2) increased. In addition, objective performance (time) and self-
rated scores improved with, at least, medium effect sizes. Social validation indicated
that participants found the training to be rewarding, and in line with the study find-
ings. Such results propose further empirical research on flow training on elite ath-
letes be undertaken to assess the intensity of flow experiences and performance
scores. Future research examining retention data and education only interventions
are advised. Implications arising from the present data are discussed.
KEY WORDS: Athletes, Climbing, Intervention, Multiple-baseline training.
Introduction
Positive psychology has increasingly been used in performance arenas
(Swann, Keegan, Piggott, & Crust, 2012), focusing on using an individual’s
strength to increase performance and enjoyment. The flow state has emerged
as a dominant theme in positive psychology (Seligman, 2012) producing a
wealth of qualitative and anecdotal evidence in sport psychology that sug-
gests flow is an optimal psychological state that underpins an athlete’s most
memorable experiences (Jackson, 1996). Csikszentmihalyi’s (1990) concep-
tual theory of flow proposes nine components to a flow experience: 1) Chal-
Corresponding Author: Cameron Northworthy, Department of Sport & Exercise Science,
Spinnaker Building, Cambridge Road, Portsmouth, PO1 2ER United Kingdom (e-mail:
Cameron.norsworthy1@myport.ac.uk)
Int. J. Sport Psychol., 2017; 48: 1-00
doi: 10.7352/IJSP 2017.48.000

lenge-skills balance; 2) Merging of action and awareness; 3) Clear goals; 4)
Unambiguous feedback; 5) Concentration on the task at hand; 6) Sense of
control; 7) Loss of self-consciousness; 8) Transformation of time; and 9)
Autotelic experience (Jackson & Csikszentmihalyi, 1999). The flow model
has proven robust across lines of culture, class, gender and sport (Nakamura
& Csikszentmihalyi, 2002). This state differs from an alternative emerging
peak performance state, the clutch state, in which individuals perform under
pressure through similar dimensional experiences but differentiates itself
from flow through the deliberate concentration, intense effort, and height-
ened awareness described by participants (Swann, Crust, Jackman, Vella,
Allen, & Keegan, 2017).
Due to the association between flow and peak performance (Jackson &
Roberts, 1992) and mental toughness (Crust & Swann, 2013), understanding
and attaining flow is of great interest practically to athletes (Pain, Harwood,
& Anderson, 2011). Although flow has been both positively correlated with
performance in tennis players (Flett, 2015), and linked to increases in flow
with performance (e.g., Nakamura & Csikszentmihalyi, 2014; Pates, Oliver,
& Maynard, 2001), the flow state is a distinct concept from the outcomes of
peak performance (i.e. winning) and the emotions of peak experiences
(Harmison, 2011). For example, one can perform well but not be in an opti-
mal state of flow (Jackson & Csikszentmihalyi, 1999). Whilst performance
may be expected to increase during flow due to common descriptors, such as
high levels of concentration, clear goals, unambiguous feedback, and a sense
of control (Jackson & Csikszentmihalyi, 1999), applied performance strate-
gies do not always promote flow descriptors such as loss of self-conscious-
ness, action and awareness merging, transformation of time and autotelic
experience (e.g., Peters, 2013). Thus, indicating what constitutes flow train-
ing may be similar but not identical to training for peak performance or
clutch states. For example, peak performance training is often focused
towards performance goals and achieving outcomes (Filby, Maynard, &
Graydon, 1999), whereas flow training may be more focused towards elicit-
ing intrinsic motivation or flow antecedents (Jackson, Thomas, Marsh, &
Smethurst, 2001).
A multitude of literature exists examining performance enhancement
strategies (Weinberg & Gould, 2014), however, other than Swann et al.’s
(2012) systematic review on flow state research in elite athletes, little infor-
mation collating research surrounding how flow experiences can be manipu-
lated and enhanced is available. Additionally, Swann et al. (2012) found that
the majority of athletes reported flow to be controllable (72%) and restor-
able (81%). Common psychological interventions such as arousal regulation,
2C. Norsworthy et al.

goal setting, self-talk, and imagery on flow have reported mixed results in
enhancing flow states (Nicholls, Polman & Holt; 2005; Pain, Harwood &
Anderson, 2011; Pates, Cowen & Karageorghis, 2012; Koehn, Morris &
Watt, 2014), whilst interventions using hypnosis on cyclists (Lindsay, May-
nard & Thomas, 2005) and golfers (Pates, 2013), and imagery combined with
music on soccer players (Pain et al., 2011), have reported positive results.
However, all these studies were pre-experimental designs not sampling large-
scale randomized controlled trials. Contrarily, mindfulness interventions
(e.g., Bell, 2015; Schwanhausser, 2009) have had perhaps the most influential
training on flow to date, with Aherne, Moran, and Lonsdale (2011) finding a
significant interaction with global scores of flow intensity across a variety of
sports. Recommendations to date, for future research examining flow inter-
ventions, include the use of multi-faceted approaches to match skills to flow
dimension (Swann et al., 2012), and concurrent methods of cognitive
restructuring to ensure the training is both well understood and able to be
applied (Lindsay et al., 2005). Additionally, Lindsay, Maynard, and Thomas
(2005) suggested that future research use multiple control groups in order to
differentiate training towards flow and performance. To the date of publica-
tion, only two studies have examined a multi-skilled approach to flow (Judge,
Bell, Bellar, & Wanless, 2010; Reardon & Gordin, 1999), though, both were
descriptive and did not test participants. This limited research is surprising
considering the mindset accompanying flow pushes athletes to their maxi-
mum performance limits (Jackson & Csikszentmihalyi, 1999). Furthermore,
Williams and Krane (1998) suggest that a psychological profile congruent
with the dimensions of flow correlated with flow, and an autotelic personal-
ity is more amenable to finding flow (Nakamura & Csikszentmihalyi, 2014).
Therefore, this study aims to develop a multi-faceted flow intervention and
assess its impact on flow states and performance in elite athletes.
To increase intervention effectiveness and pre-establish potential influ-
encing factors (Swann et al., 2012), the study’s evidence base for intervention
selection and their associated dimensions of flow will now be described.
Goal orientation (Aubé, Brunelle, & Rousseau, 2014) and a process-orien-
tated focus (Jackson & Roberts, 1992) have been stated as important psy-
chological factors to attaining flow. Therefore, the multi-facets of flow train-
ing will directly target the flow dimensions and the process of being in flow
as the primary goal, over and above performance outcomes. Csikszentmiha-
lyi’s (1997) has stated that consciously being aware of flow during the activ-
ity is counterproductive and inhibits one’s ability to merge action and aware-
ness. Thus it is important that the training focuses on one’s intention to find
flow before the activity and not one’s necessity to consciously think about
Flow training 3

finding flow continuously during the performance. In order to meet Lindsay
et al.’s (2005) recommendation of concurrent methods of cognitive restruc-
turing and Holliday, Burton, Sun, Hammermeister, Naylor, and Freigang’s
(2008) proposal that education is an integral part of mental skills training and
necessary for participants to cognitively understand flow, an education on
flow and dimensional importance will initiate. After which, to adhere to
Nakamura and Csikszentmihalyi’s (2014) conditions of flow (i.e. clear goals
and an adequate challenge that matches perceived skill) participants’ goals
will be examined to integrate flow as the primary goal to their performances.
To ensure a focus towards finding flow is continued during the performance
and facilitates the dimension ‘concentration on task at hand’ as outlined by
Judge et al. (2010), participants’ self-talk during the performance will be
examined and redirected towards finding flow and concentrating on the task
at hand. .Mindfulness interventions have been reported to strongly affect
dimensions ‘concentration’, ‘clear goals’, ‘sense of control’, ‘unambiguous
feedback’, and ‘loss of self-consciousness’ (Aherne et al., 2011; Cathcart et
al., 2014); the explanation being that through increased awareness, we learn
to regulate attentional processes towards more relevant information for the
task at hand (Gardner & Moore, 2007), thus positively impacting one’s deci-
sion-making and perception of the integral ‘challenge-skill balance’ enabling
a higher degree of self-efficacy (Pineau, Glass, Kaufman, & Bernal, 2014).
Therefore, a mindfulness intervention aimed at re-directing attention when
distracting thoughts occur towards finding flow will be deployed. Lastly, to
adhere to Pain et al.’s (2011) recommendations regarding flow interventions,
objective as well as subjective performance measures will be assessed.
In summary, the main purpose of this study is to examine the effects of a
multi-faceted flow training program on flow states and objective and subjec-
tive performance scores in elite athletes. Further, as this study is breaking
new ground by applying a flow training program on participants for the first
time, it will attempt to develop the knowledge and understanding of practi-
cally developing and applying a flow training program.
Method
PARTICIPANTS
Four elite rock-climbers (age range = 38-44 years; mean = 41 years), based within the
United Kingdom took part in the study. Elite status was contextualised by climbers adhering
to Swann, Moran, and Piggott’s (2015) designation of elite athletes and achieving the grade of
6b or above in the British sport climbing grading system.
4C. Norsworthy et al.

Flow training 5
DEPENDENT VARIABLES
The three dependent variables were flow intensity, self-rated performance, and timed per-
formance. Global and dimensional flow intensity was measured using the Flow State Scale-2
(FFS-2) (Jackson & Eklund, 2002). The FFS-2 measures the intensity of flow experienced
through a 36-item questionnaire self-scored on a 5-point Likert scale ranging from 1 = ‘strongly
disagree’ to 5 = ‘strongly agree’ targeting the nine components of flow (Jackson & Csikszent-
mihalyi, 1999). The FFS-2 has produced acceptable reliability and internal consistency (alphas
0.80) scores (Jackson & Eklund, 2002). Participants scoring above a 3.4 score were deemed in
flow, as suggested by Kawabata and Mallett’s (2016) series of latent class factor analyses. Sub-
jective performance scores were self-scored on a 20-point scale ranging from 1 = ‘terrible’ to 20
= ‘outstanding’. Objective performance scores were assessed using the climb time.
RESEARCH DESIGN
To examine the effects of a multi-skilled flow intervention on flow states and perfor-
mance, a single-subject multiple baseline design (Martin & Pear, 2003; Thelwell & Greenlees,
2003) was adopted. The study had multiple interventions and no reversal, as adopted by Pain
et al. (2011). The participants acted as their own control, and testing took place over a nine-
week period. Since three dependent variables were employed, with flow scores consisting of
nine further dimensions, the team made an ‘a priori’ decision to introduce the first interven-
tion after four data points rather than introducing the interventions after a stable baseline or
scores moving in an opposite direction (Kazdin, 1992). Deciding on a ‘primary’ dependent
variable to determine intervention timing would undermine the other variables and flow
dimensional importance, and was therefore deemed inappropriate (Thelwell, Greenlees, &
Weston, 2006). Interventions followed after every two data points, except intervention 1 (edu-
cation) which was given extra data points for retention testing as the effects of flow education
had not been reported to date. Additionally, two extra data points were undertaken at the end
of the study to examine retention scores.
FLOW TRAINING PROGRAM
A training program including an education, goal-setting, self-talk, and mindfulness inter-
vention to facilitate flow was delivered to each participant individually by the researcher and
overseen by two Health Care and Professions Council (HCPC) registered Sport and Exercise
Psychologists.
The education on flow was delivered in three pre-recorded video presentations, totaling
two hours in length. The video content included descriptions of Csikszentmihalyi’s (1990)
nine flow dimension definitions, Jackson’s (1996) applied dimensions to flow, summaries of
flow research, anecdotal evidence describing the experience of elite athletes in flow, scenario
based examples where an athlete might choose a higher order goal towards flow rather than
performance focused outcomes. The videos were delivered in a lecture format. Within two
days of viewing each of the videos twice, a debrief session was facilitated through online video
software to facilitate questions on flow only, and test whether learning was retained.

The goal-setting intervention to adopt flow as the primary goal was delivered during a
one-to-one session lasting approximately forty minutes over online video software. The con-
tent of the goals was participant-led to ensure autonomy (Csikszentmihalyi, 1990; Deci &
Ryan, 2000), whilst the goal-setting structure was pre-determined starting with a higher order
goal (flow) that generated multiple process goals (Grant, 2016) aligned with prioritising flow.
The researcher facilitated the session to ensure goals were congruent with other areas of their
lives (Wesson & Boniwell, 2007) and then integrated into their positive pre-performance rit-
ual (Jackson, 1992).
Self-talk was examined to identify negative self-talk and reconstruct functional short
phrases (Ellis, 1999) from self-generated positive keywords (Jackson, 1992) targeted towards
prioritizing flow. Scenarios were then addressed with the client for practical application,
whilst providing an opportunity to fine-tune appropriate self-talk (Thelwell, et al., 2006).
Lastly, participants were asked to listen to three 20-minute mindfulness recordings.
Adherence was managed through text and email communication. The recordings were
scripted on the ‘breath, body and mountain’, ‘body scan’ and ‘standing yoga’ work of Kabat-
Zinn (Teasdale & Segal, 2007) that both Gardner and Moore (2004) and Aherne et al. (2011)
successfully employed during their flow studies. Script adaptation included flow descriptions
from the education on flow and directing the participants’ attention towards flow.
PROCEDURES
Prior to the recruitment of participants, institutional ethical approval was formally
received from the institution of the lead author. Volunteer participants were recruited through
the emailing of various rock-climbing clubs within the UK. All engaged participants claimed
to have minimal prior knowledge on flow when asked to share their existing knowledge of
flow during the recruitment process. One participant was excluded from the study before
commencing as their level of knowledge on flow already included dimensional clarification
and had claimed to read two books on flow. All participants volunteered for the study, signed
informed consent forms prior to commencement, and were informed that all data would
remain confidential. Indoor rock climbing was deemed an appropriate activity as influencing
external factors such as environmental conditions could be controlled, performances could be
easily replicated, and assessments could be immediately conducted post-performance. Inter-
ested participants were sent a participant information sheet and consent form via email, then
followed up via video software to answer questions and ensure participants understood the
study’s practicalities. Participants chose an indoor climbing route that was self-assessed as
challenging but possible, and practiced the route for a week to minimise effects such as famil-
iarity or technical improvements. After which, twice a week, the participant performed a
timed ascent after warming-up. Where possible, participants kept the same belayer (assistant)
who was responsible for measuring time with a stopwatch. Flow and performance scales were
completed independently by the participant immediately after route completion for best prac-
tice (Jackson & Eklund, 2002). Climb time was revealed to the participant by the belayer after
questionnaire completion to ensure objective performance scores did not affect flow scores or
subjective performance scores (Koehn, Morris, & Watt, 2014). Completed scales and forms
were scanned and emailed on the day to the researcher, bar a few exceptions due to limited
internet access. Contact with participants during the study was kept to a minimum and inter-
ventions were delivered after the same number of climbs, as opposed to a fixed time frame to
6C. Norsworthy et al.

Flow training 7
increase procedural reliability (see Figure 1 for sequencing). Each participant was debriefed
via video software after social validation procedures.
SOCIAL VALIDATION
Social validation questions were collected to assess reactions to treatment procedures
and experimental outcomes (Pates, Maynard, & Westbury, 2001). Questions included: “Do
you feel the training increased your flow experiences (intensity)? Do you feel the training
improved your ability to find flow (frequency)? Do you feel the training increased your
flow experiences (intensity)? Overall how helpful was the training? Do you feel the train-
ing was professional?” Additionally, during the post study debrief informal discussions
were held between the participants and lead researcher to elicit any additional effects of
the training.
Fig. 1. - Flow state scores for participant 1-4. Each vertical line indicates an inter-
vention. M = total mean score for that period.
0
20
40
60
80
100
120
140
160
180
200
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
Global Flow Scores
Climbs
Participant 1 Participant 2 Participant 3 Participant 4
pp
M= 118.12
M= 135.58
M= 147.75
M= 153.12
M= 164
Education
Goal - Setting Self -talk Mindfulness

DATA ANALYSIS
Visual inspection recommendations by Martin and Pear (2003) and Hrycaiko and Mar-
tin (1996) were followed to determine the confidence of the training effect on the dependent
variables. Confidence was enhanced: (a) when baseline performance is stable or in a direction
opposite to that predicted for the treatment, (b) the greater the number of times that an effect
is replicated both within and across subjects; (c) the fewer the number of overlapping data
points between baseline and treatment phase; (d) the sooner the effect occurs following the
introduction of treatment; and, (e) the larger the size of the effect in comparison with baseline
(Pain et al., 2011). Following, effect size calculation (d) of intervention effect (mean baseline
scores minus mean intervention scores, divided by standard deviation of data in baseline) was
conducted, in which < .87 = small effect, .87 to 2.67 = medium effect, and > 2.67 = large effect
(Parker & Vannest, 2009).
Results
FLOW ANALYSIS
Flow scores for the study period are presented in Figure 1 and Table I.
Participant 1 increased mean flow scores by 23% (d= 3.42) post-interven-
tion with four overlapping data points; participant 2 by 47% (d= 6.56) with
one overlapping data point that may have been affected by a reported illness;
participant 3 by 15% (d= 1.3) with four overlapping data points; and partic-
ipant 4 by 29% (d= 1.3) with three overlapping data points. All participants
showed a stable baseline and an immediate improvement after intervention 1
and mean increases on interventions 1 (M = 21.52%), 2 (M = 0.97%) after, 3
(M = 2.95%) after and 4 (M = 3.26%). Across participants mean global flow
scores increased by 28.5%.
Flow dimensional analysis revealed increases for all dimensions post-
training, except for ‘transformation of time’ from participant 2 (Table II).
Specific interventions did not always increase associated dimensional scores
as expected. Interventions resulted in an escalating positive effect on flow
scores (Table III).
8C. Norsworthy et al.
TABLE I
Mean Effect Sizes (d) of Flow State Scores Post-Intervention
Global Flow Participants
12 3 4Total Mean
Effect Size 1.30 6.56 1.30 3.42 3.14
Medium Large Medium Large Large

Flow training 9
It is worth noting that all participants met Kawabata and Mallett’s (2016)
proposal that the scores of the three proximal dimensions (challenge-skills
balance, clear goals, unambiguous feedback) have to be above 3.4 to identify
individuals as experiencing flow.
TIMED PERFORMANCE ANALYSIS
The impact of the intervention on timed performance is shown in Figure
2, and Table IV
. Participant 1 decreased mean climb time by 47% (d= -1.19)
TABLE III
Individual Intervention Mean Increases between Baseline and Intervention Data
Interventions
Education Goal-Setting Self-Talk Mindfulness
%d%d%d%d
15% 0.86 26% 1.67 31% 2.12 75% 5.07
Small Med Med Large
% = % difference from baseline data; d = effect size difference from baseline data
TABLE II
Mean Effect Sizes (d) of Flow State Dimensional Scores Post-Intervention
Flow Dimensions Participants
12 3 4Total Effect Mean
Skill-Challenge 0.58 2.02 0.75 1.99 1.34
Small Medium Small Medium Medium
Action/Awareness 0.70 6.60 1.93 5.92 3.79
Small Large Medium Large Large
Clear Goals 1.09 2.74 0.36 5.77 2.49
Medium Large Small Large Medium
Unambiguous Feedback 9.58 2.00 1.19 5.51 4.57
Large Medium Medium Large Large
Concentration 3.63 18.63 3.27 12.31 9.46
Large Large Large Large Large
Control 1.53 5.64 1.53 1.64 2.59
Medium Large Medium Medium Medium
Self-Consciousness 1.61 2.36 -1.67 0.64 0.73
Medium Medium Medium Small Small
Transformation of Time 0.62 -0.01 24.38 7.11 8.02
Small None Large Large Large
Autotelic 1.48 0.86 1.77 0.85 1.24
Medium Small Medium Small Medium

post-intervention with no overlapping data points; participant 2 by 57% (d=
-2.05) with one overlapping data point that may have been affected by a
reported illness; participant 3 by 69% (d= -2.02) with one overlapping data
point; and participant 4 by 74% (d= -3.42) with no overlapping data points.
Participant 1 and 2 showed stable baselines, whilst 3 and 4 were relatively
stable. All participants showed an immediate improvement after intervention
10 C. Norsworthy et al.
Fig. 2. - Timed scores for participant 1-4. Each vertical line indicates an intervention.
M = mean score for that period.
!
0
2
4
6
8
10
12
14
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
Climb Time
Climb
M=6.52
M=4.84
M=4.48
M=3.95
M=3.36
Participant 1 Participant 2 Participant 3 Participant 4
pp
TABLE IV
Mean Effect Sizes Of Timed Performances Post-Intervention
Time Performance Participants
12 3 4Total Mean
Effect Size -1.19 -2.05 -2.02 -3.42 -2.17
Medium Medium Medium Large Medium

Flow training 11
1 and mean increases on interventions 1 (M = 16.83%), 2 (M = 3.35%) after,
3 (M = 12.9%) after and 4 (M = 9.03%). Across participants mean timed per-
formance scores increased by 61.8%.
SELF-RATING PERFORMANCE ANALYSIS
The impact of the intervention on self-rating performance are shown in
Figure 3, and Table V. Participant 1 increased mean self-rated performance
scores by 9% (d= 0.67) post-intervention with eight overlapping data points;
participant 2 by 53% (d= 2.57) with one overlapping data point that may
Fig. 3. - Self-rated performance scores for participant 1. Each vertical line indicates
an intervention. M = total mean score.
0
5
10
15
20
25
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
Self-rated Performance
Climb
M=12.87 M=15.5 M=16.5 M=17.3 7 M=17.9
Participant 1 Participant 2 Participant 3 Participant 4
pp
TABLE V
Mean Effect Sizes Of Self-Rating Performances Post-Intervention
Self-Rating Performance Participants
1234Total Mean
Effect Size 0.67 2.57 1.20 2.14 1.65
Small Large Medium Medium Medium

have been affected by a reported illness; participant 3 by 24% (d= 1.2) with
four overlapping data points; and Participant 4 by 50% (d= 2.14) with two
overlapping data points. Participant 1 and 2 showed stable baselines, whilst
3 and 4 were relatively stable. All participants showed an immediate
improvement after intervention 1 and mean increases on interventions 1 (M
= 43.05%), 2 (M = 0.59%) after, 3 (M = 4.69%) after and 4 (M = 2.3%).
Across participants mean self-rating performance scores increased by 34%.
SOCIAL VALIDATION
Social validation was assessed via brief questionnaires on completion of
the study. All participants rated the study to be professional, helpful and
improved their performance and ability to experience flow, suggesting trust-
worthiness for the study’s findings, and efficacy of the intervention. Each par-
ticipant stated that they consistently adhered to the procedures. Additional
debrief findings included increased motivation, reduced anxiety and an
excitement to apply finding flow under different conditions and in different
activities. E.g. participant 1 stated “I didn’t feel so anxious during the per-
formance…I am excited to try this out in other areas of my life.”
Discussion
The aim of this study was to develop a multi-faceted intervention, specif-
ically designed towards adopting flow as the primary goal, and then assess its
impact on flow states and performance in elite athletes. The findings revealed
that all participants increased flow and performance scores by at least
medium effect sizes, except participant 1 whose self-rating performance
increased by a small effect size. Confidence in the findings was acceptable
using Martin and Pear’s (2003) visual recommendations and Pain et al.’s
(2011) adoption of effect size analysis on SS designs. Thus suggesting a multi-
faceted flow training program should be explored further in future research.
The findings are in line with those reported by Flett (2015) and Jackson and
Csikszentmihalyi (1999) who reported performance to increase with flow
scores. However, although both positive increases were reported for all vari-
ables the magnitude of variance potentially supports Harmison’s (2011)
notion that flow and peak performance are distinct states. Interestingly,
although the training was focused towards increasing flow states over and
above performance, objective performance scores were substantially higher
12 C. Norsworthy et al.

Flow training 13
than flow increases. A possible explanation may derive from the participant’s
comments regarding reduced anxiety and increased motivation, which may
be linked to the dimensional increases of ‘action and awareness merging’,
‘loss of self-consciousness’ and ‘autotelic experience’ that may not be ordi-
narily associated with performance training and potentially separates flow
training from performance training. However, as all the flow dimensions
increased, this report adds feasibility to the effects of flow training and
echoes Lindsay, Maynard, and Thomas’s (2005) suggestion of deploying
larger sample sizes and multiple control groups to develop more robust
future studies in this domain.
Interestingly, self-rating performance (subjective) and timed perfor-
mance (objective) scores increased at varying rates, consequently resulting in
varying relationships with flow. Closer analysis revealed that a plateauing
effect for self-ratings resulted in only marginal increases appearing towards
the later stages when subjects neared their ceiling, even when performance
times improved. Thus, the participant’s self-perception of performance levels
may have changed throughout the study and may explain the differentiation
between subjective and objective performance scores. Any conclusion of the
relationship between flow and performance is out of the scope of this study,
however, this study does urge researchers looking to further this field (see
Flett, 2015) that it would be advisable to distinguish between subjective and
objective performance measures.
Unexpectedly, specific dimensions associated with specific interven-
tions, such as ‘clear goals’ and ‘goal-setting’ (see introduction), did not
always increase directly after the associated intervention was employed.
However, global flow scores did increase for each intervention, thus suggest-
ing improvements in flow were more likely related to the adoption of flow as
a primary goal rather than the intervention methodology (e.g. generic goal
setting or mindfulness interventions) that may have otherwise skewed related
flow dimensional scores. Flow dimensional analysis was also inconsistent
with previous research suggesting that dimensions ‘loss of self-consciousness’
and ‘transformation of time’ ordinarily report smaller variations (Jackson &
Marsh, 1996).
The findings, combined with the participant’s social validation feedback,
support the notion that the mindset accompanying flow pushes athletes to
their maximum performance limits (Jackson & Csikszentmihalyi, 1999) and
flow states may be controllable (Swann et al., 2012). Additionally, this study
has added data to the void of cognitive restructuring (Lindsay et al., 2005)
and multi-skilled intervention research on flow (Swann et al., 2012). Fur-

thermore, since flow is a state of consciousness (Jackson & Csikszentmihalyi,
1999), a process that occurs during an activity, the positive results support
wider literature that associate both flow (Jackson & Roberts, 1992) and high
performance (Weinberg & Butt, 2014) states with a process-orientated focus
as opposed to an outcome-orientated focus.
This study was designed to examine the collective effects of a multi-
skilled program, however, individual intervention analysis revealed an esca-
lating positive mean increase for interventions. Also, each intervention across
all participants in global flow scores (range = 15-75%). Therefore, it is rec-
ommended that future research compare the effects of single-skilled flow
worthy of note is that all participants, except participant 3 for timed perfor-
mance, increased their mean scores for all dependent variables immediately
after the educational intervention, then decreased scores on the next data
point and subsequently increased scores to the initial level or higher. Conse-
quently, it is recommended future research investigate the effects of educa-
tion only interventions to further understand this pattern and assess whether
flow education alone has a positive impact practically on flow and perfor-
mance within athletes and other performance arenas. Assessing education
only interventions more rigorously would help to determine whether the pos-
itive effects where due to cognitive restructuring or a participant’s inclination
to score differently on the flow scales after being exposed to them. Indeed,
regarding the practical application of sport psychology, disseminating an
educational program may prove far more efficient both financially and in
terms of time management than the continual involvement of sport psychol-
ogists; although customized support will always be applicable in certain cir-
cumstances.
Since the study directed each intervention towards finding flow and col-
lectively adopted a multi-skilled approach, it is difficult to conclusively sup-
port previous research that found positive effects on individual skills, such as
Wessen and Boniwell’s (2007) congruent goal-setting and Aherne et al.’s
(2011) mindfulness intervention. Therefore, in order to further develop flow
training that is effective and practically applicable to athletes, it is advised
future research compare the flow training employed in this study to inter-
ventions that have previously reported positive results (see Swann et al.,
2012).
A weakness of this study is the use of limited data points during baseline
and between interventions. Future research may address this by reducing the
number of dependent variables and interventions or increasing the study
duration, thus creating capacity for further data points. Another weakness is
14 C. Norsworthy et al.

Flow training 15
the use of retrospective self-reports to measure flow as previously questioned
by Jackson (2000), however, no non-retrospective alternative exists to date.
Additionally, as the researcher was not present during the moment of data
collection a level of trust towards procedural compliance was employed,
which could be scrutinised; measures for procedural clarity such as clear
briefs, text reminders and requests for participant assurances were deployed,
thus participants were deemed to have abided by the procedures. A further
weakness was evident from the social validation procedures when participant
3 stated that in hindsight the chosen climb could have been more challenging
and thus limited his intensity of flow. Participant 3 reported the lowest
increase in flow scores (15%), therefore, it is recommended future research
confirm whether the activity is sufficiently challenging after initial practice.
A limitation of this study is the transferability of findings to other
domains. Indoor rock-climbing was chosen to reduce the effect of external
variables, and although ecological to indoor rock climbers, participant 2, 3
and 4 stated their excitement of transferring these skills to climbing out-
doors. In line with this participant feedback, it is recommended future stud-
ies assess larger samples in a multitude of settings including other domains,
to determine causality and generalizability. Furthermore, it is suggested
future studies employ a control group and a performance training group, to
add greater rigor in the assessment of flow training over peak performance
training. A final limitation to the intervention’s validity is a lack of retention
data. The participants’ schedules and local gyms did not facilitate follow-up
data on various time points post intervention however this would clearly be
beneficial.
The study’s findings and positive participant feedback on professional-
ism and methodology suggest the study’s adopted interventions are a positive
starting point to developing a flow training program. The study adds detailed
information to an otherwise scant area of research. In an applied setting these
findings may seem exciting, however, the training employed is elementary
thus it is important some guidelines are outlined for interested practitioners.
Flow is an easily misunderstood concept (Hytönen-Ng, 2016) therefore
it is advised that the educational intervention on flow is a) based on reputable
flow research and b) embedded within the participants on completion. It is
recommended that tests and sessions to assess learning quality be carried out
to ensure participants are not focused on similar but varying concepts such
as peak performance or peak experience. For example, participant 3 high-
lights the benefits of an education on flow “I made gains in how to attain flow
state, if for no other reason than I understand it better now and can recognise

it better.” Equally, it is important that subsequent interventions, such as goal-
setting or self-talk, are focused towards attaining flow states and not peak
performance. Furthermore, and congruent with Csikszentmihalyi’s (1990)
notion that if the subject is consciously thinking about flow it is contradictory
to the flow experience of action and awareness merging and loss of self-con-
sciousness, flow training must direct focus and preparation towards flow and
not be a necessary consumption of conscious thought throughout the perfor-
mance. This confusion occurred for 3 out of 4 participants and may have lim-
ited initial positive results. Also, during this study participants found it help-
ful to integrate their flow-orientated goals and self-talk into their rituals,
thereby ensuring finding flow was reinforced at multiple stages before their
performance. Finally, it must be noted that the current study was applied to
individuals as opposed to teams. Personal goals towards flow may conflict to
that of differing team goals and be detrimental to a collective flow or perfor-
mance, thus team application requires further research.
To conclude, the findings indicated that flow training warrants further
research. Future research is advised to examine education only interventions,
include retention data, and report further development and refinement on
the evidence-based implications for professional practice of flow training
presented in this study.
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