An Examination of Flow State Occurrence in College Athletes.
Russell, William D.
This study examined qualitative and quantitative aspects of flow
within a group of college-age athletes. Forty-two athletes (27 males and
15 females) representing team sports (n = 28) (football, baseball,
volleyball, softball, and basketball) and individual sports (n = 14)
(swimming, track, wrestling, and triathlon) were interviewed on what
factors they felt helped, prevented, and disrupted flow occurrence.
Previous qualitative flow examination was extended (Jackson, 1995) and
an interview format was developed in which an inductive analysis was
performed Raw data which were integrated into higher order themes and
general dimensions resulted in nine factors helping flow, eight
dimensions preventing flow, and six dimensions disrupting flow that
synthesized the 148 themes suggested by the athletes. Results of the
qualitative analysis revealed marked overlap to previous qualitative
results, however this sample perceived flow to be less controllable than
elite athletes. In addition, these athletes completed the Fl ow State
Scale (Jackson & Marsh, 1996) to obtain a quantitative assessment of
flow relationships. Results of a two-way MANOVA (gender x sport type) on
FSS subscales resulted in a nonsignificant interaction (p =.62) and
nonsignificant main effects for gender (p =.45) and sport type (p =.11).
In addition, separate two-ANOVAs performed on FSS subscales and total
FSS scores with Bonferroni test to correct for family-wise error rate,
indicated only one significant main effect for sport within the
action-awareness subscale (F=9.62, p =.004). College athletes appear to
have similar experiences of flow states, regardless of gender or sport
type. Results are discussed in terms of the importance of examining both
qualitative and quantitative aspects of flow occurrence in athletes.
Flow has been described as a state of optimal experience
(Csikszentmihalyi, 1990) involving total absorption in a task at hand,
and creation of a state of mind where optimal performance is capable of
occurring. Csikszentmihalyi (1990) argued that there are particular
activities that are more likely to produce flow, and personal traits
that help people achieve flow more easily. A critical qualification of
this state is that flow is not dependent upon the objective nature of
challenges or the objective level of one's skills, but that flow is
entirely dependent on one's perception of the challenges and their
skill (Csikzentmihalyi, 1975). Recent research has examined possible
associations between flow state and athletic performance (Jackson,
Kimiecik, Ford, & Marsh, 1998; Jackson, 1992, 1993, 1995; Jackson
& Roberts, 1992; Stein, Kimiecik, Daniels, & Jackson, 1995). The
apparent association between flow state and peak performance (Jackson,
1992, 1993; Jackson & Roberts, 1992; Privette & Bundrick, 1991)
makes un derstanding flow tantamount to the athlete, coach, and sport
psychologist. Knowledge gained of these factors is important in helping
athletes to prepare for optimal performance.
In explaining predispositions to experience flow, Csikzentmihalyi
(1990) argued that particular activities that are more likely to produce
flow, traits that assist in producing flow, and that there is a link
between peak performance and peak experience (McInnman & Grove,
1991). Specifically, Csikzentmihalyi (1975) indicated that a
skill-challenge balance was an essential precursor flow occurrence, and
that flow was dependent upon the individual's ability to structure
their consciousness so as to make flow possible. The complexities in
examining flow relate to the concerns over qualitative and quantitative
research approaches (Jackson & Marsh, 1996), yet the ability to
effectively incorporate these approaches to the study of flow may have
implications for applied sport psychology consultants. By identifying
the psychological factors that enhance, inhibit, and disrupt flow,
consultants and coaches may be better able to help athletes achieve
optimal performance (Kimiecik & Stein, 1992).
Jackson (1992) provided information from in-depth interviews with
elite figure skaters about specific factors related to flow occurrence.
These skaters indicated that flow was facilitated by positive mental
attitude, positive pre-competitive and competitive affect, maintaining
appropriate focus, physical readiness, and partner unity. Factors
perceived to prevent or disrupt flow were physical problems/mistakes,
inability to maintain focus, negative mental attitude, and lack of
audience response. Jackson (1995) later examined athletes'
responses to questions about what facilitated, prevented, and disrupted
flow in 28 elite athletes from seven different sports. Results of
interview responses revealed 10 dimensions and included salient factors
such as physical and mental preparation, confidence, focus, how
performance felt, and optimal motivation, and arousal. In addition, 79%
of the athletes surveyed felt that factors facilitating or preventing
flow were perceived as controllable.
Jackson (1996) recently investigated athletes responses and found
correspondence between dimensions of flow described by Csikzentmihalyi
(1990) and athletes descriptions of their flow experiences. Through
qualitative analysis of athletes interviews, those dimensions of flow
represented most across the group's data were the autotelic experience of flow, total concentration on the task at hand, merging of
action and awareness, and the paradox of control (Jackson, 1996). The
autotelic dimension of flow has been defined as an intrinsically motivating participation in an activity for it's own sake and is an
aggregate of all other flow dimensions (Jackson, 1996). One consistent
finding has been that when the activity was perceived as enjoyable,
athletes described their state of mind in similar terms (Jackson &
Csiksentmihalyi. 1999). Jackson, Kimiecik, Ford & Marsh (1998)
recently examined psychological correlates within trait and state flow.
Results provided support for the construct of flow in that similar sets
of predictor variables explained significant relationships with flow at
both the subscale and global level. Specific predictors were perceived
ability, anxiety, concentration disruption, anxiety-worry and intrinsic motivation to experience stimulation. Support for construct validity of
flow scales was also demonstrated in that the flow trait challenge-skill
balance was most highly correlated with the trait measure of perceived
ability, and the authors concluded that high perceived ability is
crucial to facilitating flow states (Kimiecik et al., 1998). It may be
that less-skilled athletes are less likely to experience flow because
both their actual and perceived level of skill are lower than elite
athletes.
In an effort to quantitatively study flow, the Flow State Scale
(FSS; Jackson & Marsh, 1996) was developed. The nine FSS scales of
the 36-item instrument represent Csikzentmihalhi's (1990) nine
dimensions of flow and each dimension is measured by four items. The
approach in developing the FSS was to establish construct validity of an
inventory designed to measure flow as a hypothetical construct.
Confirmatory factor analysis supported the nine scales and a
hierarchical model in which one global flow factor explained
correlations between the nine FSS factors. Internal consistency estimates for the FSS scales were satisfactory (alpha M = .83). The
usefulness of a single global score compared to the set of nine FSS
scores was not determined. In addition, it was proposed that future
research use the FSS in determining various group differences (Jackson
& Marsh, 1996).
Conceptual and methodological issues related to flow research have
been noted (Kimiecik & Stein, 1992). Conceptual concerns such the
nature of flow and how it occurs have been addressed in qualitative
analyses of the flow concept (Jackson, 1995, 1996), yet other personal
and situational variables such as gender and sport setting remain
largely unexamined in their relationship with flow occurrence. Use of
the FSS may help to clarify the qualitative relationships and complex
construct of this concept.
The richness of the flow construct necessitates that measures are
inclusive and incorporate both qualitative and quantitative approaches.
Several dimensions of flow have been theoretically discussed and
supported by research (Jackson, 1995, 1996; Jackson & Marsh, 1996;
Jackson et al., 1998). In addition, sport and exercise psychology
research has recognized the need for multidimensional and sport-specific
measurements (Gill, Dzewaltowski, & Deeter, 1988; Vealey, 1986).
Therefore, in order for researchers to assess flow in a more systematic
fashion, it is necessary to incorporate quantitative assessment of this
construct into investigation that may delineate systematic relationships
between potential antecedents of flow.
The purposes of this study were to (a) determine whether
differences existed across gender or sport setting with regard to
factors important to flow state, as measured by the Flow State Scale
(Jackson & Marsh, 1996) and (b) extend the work of previous
qualitative study of flow (Jackson, 1992,1995,1996) by examining factors
which were relevant to helping, preventing, and disrupting flow in a
sample of male and female college athletes from team and individual
sports.
Method
Participants
Fifty male and 50 female college athletes were identified from a
large Midwest university and were sent a letter asking if they would
volunteer to participate in a study assessing psychological factors
related to athletic performance. Athletes who responded to a letter of
invitation asking if they would be willing to be interviewed about
optimal sport experiences were included. The number of participants was
the result of maximizing the overall N and an attempt was made to obtain
equal males and females. The final number of participants in this study
was 42 college-age athletes (27 males, 15 females). The mean age for
participants was M = 20.43, SD = 1.99 with a range of 17 to 27 years.
Athletes represented a range of different sports including team sports
of football, baseball, volleyball, softball, and basketball (n = 28) and
individual sport athletes of swimming, track, and wrestling (n = 14). In
addition, one college student who was solicited was a national level
triathlete, and based upon precedence fro m pervious flow study
(Jackson, 1995, 1996) was included in this study as an individual sport
athlete.
Instruments
Part I: Quantitative Analysis-flow State Scale. The 36-item
instrument of the Flow State Scale (Jackson & Marsh, 1996) was
administered to athletes after their qualitative interviews. The Flow
State Scale measures nine separate dimensions within flow, based upon
previous qualitative analyses (Jackson, 1995) with elite athletes.
Internal consistency estimates for the nine scales have been reasonable
(M= .83) and confirmatory factor analysis has shown support for the nine
scales (Jackson & Marsh, 1996). In constructing the Flow State
Scale, Jackson and Marsh (1996) indicated support for the
multidimensionality of the flow construct by support of nine first-order factor model. In addition, the nine scales had reliabilities of at least
.80, satisfying criteria for acceptable reliability.
Part II: Qualitative Analysis -Interview Guide. Following previous
flow research formats (Csikszentmihalyi, 1975; Jackson, 1995) an
interview was developed to provide detailed qualitative analysis of
factors associated with flow state. Similar to Jackson's (1995)
format, athletes were first asked to describe a performance in which
he/she was in flow (This state was not identified to athletes as flow,
but performances which were optimal or near optimal and were enjoyable).
Athletes were subsequently asked three specific questions about flow:
what factors help you to achieve flow, what are factors that prevent
flow, and what disrupts flow during performance. After discussing
factors that were believed to affect flow, athletes were also asked
whether they perceived they could control these factors.
Procedures and Analyses
An interview guide was pilot tested on two college athletes not
used in the current study to verify item clarity. All interviews were
conducted face-to-face and were transcribed verbatim in preparation for
data analysis. The interview procedure was more condensed than previous
flow investigation (Jackson, 1995) as interviews lasted on average
between thirty minutes to an hour due to the focus on the specific
recall of performance during flow. After transcripts were finished,
interview responses were read and transcribed into themes, and later
compiled into sets of raw data themes (one set per question). These
themes were quotes or paraphrases that described lengthy quotes.
Part I: Quantitative Analysis - Flow State Scale. A multivariate
analysis of variance MANOVA (gender x sport setting) was conducted using
gender and sport setting (individual and team sport) as independent
variables and the nine FSS subscales and total FSS score as dependent
variables. The interest within this study was to examine the
multidimensional nature of the FSS. However, Jackson and Marsh (1996)
indicated the possibility that distinct flow profiles of specific flow
components could have important differences, yet result in the same
global score. It is feasible that while no multivariate relationships
are evident, meaningful univariate relationships may still yield
important information on how athletes differ across gender and sport
setting in specific flow-related components.
Therefore, an a priori decision was made to examine FSS subscales
using a two-way (gender by sport setting) MANOVA, with follow up
discriminant analyses on significant interactions and main effects. A
decision was also made that if no significant MANOVA results were found,
separate two-way ANOVAs (gender by sport setting) on the nine FSS scores
and total FSS would be analyzed. The rationale for this analysis was
that while the multivariate relationship among the flow components may
be nonsignificant, meaningful information may still be gained by
determining differences across gender and sport setting for each
individual component of flow. Since Jackson and Marsh (1996) have
posited that the relative usefulness of global and specific components
of FSS responses cannot be evaluated until the FSS instrument has been
more extensively used and validated, both analyses were deemed
appropriate. A family wise alpha level of .01 was adopted for all
analyses and a Bonferroni correction was used to prevent alpha level
inflation. Since the examination of gender and sport setting using the
FSS was exploratory in nature, no specific hypotheses were adopted.
Part II: Qualitative Analysis - Inductive Content Analysis. Jackson
(1996) has highlighted the importance of rich description of qualitative
analysis that is inherently important to examining flow. Thus, inductive
analysis (Jackson, 1995) was used to assess factors helping, preventing,
and disrupting flow in this sample of athletes. The inductive analysis
was used to integrate thoughts expressed by athletes into more coherent
themes that link thoughts into higher order themes. This process
involved examining raw themes and comparing them with all other themes
at a particular level, integrating themes with similar meaning while
separating themes with different meaning.
Three by five index cards were used to record raw data themes in
order to organize the inductive analysis process. The initial level of
qualitative analysis involved using the athletes' direct quotes,
enabling a more valid description to depict this data theme, based
directly on what athletes said. The entire quotation was written on one
side on the card, and the summary statement was written on the other
side. The reliability of the inductive content process was verified by
having a person independent of this study examine all the cards to
verify that summary statements accurately reflected athletes'
quotations. Once this initial list of raw themes was complete, an
inductive analysis was performed to generate a set of higher order
themes for each question. Finally, a second inductive analysis was
performed to further integrate themes into more general dimensions,
which were used to put together a larger number of athletes' ideas
to promote a further abstraction of specific themes.
As part of this qualitative analysis, methods for establishing data
trustworthiness were deemed appropriate (Jackson, 1995) and it has been
noted that use of certain techniques and careful analysis of data
ensures greater credibility (Patton, 1990). This process included (a)
detailed description in the data collection and analysis, (b) a
reflexive journal which included detailed aspects of the logistics of
the study, including decisions made during the study, their rationale,
and (c) the involvement of three separate individuals including a peer
debriefer, a reliability checker, and an auditor to form the basis of
increasing truth value and transferability of the data (Lincoln &
Guba, 1985). The peer debriefer helped to identify biases and clarify
interpretations of inquiry. The external checker clarified decisions on
independent checking of data themes and their higher order themes
compared to the investigator. The auditor examined all relevant
documents pertaining to this study, providing verification of t he
acceptability of the conclusions.
Results
Part I Quantitative Analysis- Flow State Scale
Results of the overall two-way (gender x sport setting) MANOVA
resulted in a nonsignificant interaction (p = .62) and nonsignificant
main effects for gender (p = .45) and sport setting (p = .11). As a
result of the nonsignificant multivariate effects on FSS subscales,
separate 2-way ANOVAs (gender x sport setting) were performed on the
nine FSS subscales and global FSS scores to examine potential univariate
effects on the individual flow state subscales.
Two-way ANOVA results indicated nonsignificant gender by sport
interactions and nonsignifiacnt main effects for the Flow State Scales
of challenge-skill balance, clear goals, unambiguous feedback, paradox
of control, loss of self-confidence, transformation of time, autotelic
experience, and total FSS score. For action-awareness, the interaction
was nonsignificant (p = .71) as was the main effect for gender (p =
.12). However, there was a significant main effect for spot setting
F(1,38) = 9.62, p = .004, indicating that team-sport athletes has a
significantly higher level of action-awareness merging than individual
sport athletes during flow. For the concentration subscale, there were
trends toward significance on the interaction (p = .051), the gender
main effect (p = .054) and the sport main effect (p = .03) which fell
short of statistical significance at the .01 level under the family-wise
Bonferroni alpha level. Interrcorrelations among FSS scores and global
scores are indicated in Table 1. Intercorrelati ons between global FSS
scores and FSS subscales ranged from r = .41 (concentration of task at
hand) to r = .76 (paradox of control) and were significant (p [less
than] .005), except for clear goals (r .21, p = .19) and transformation
of time (r = .12, p = .45). Intercorrelations between the higher order
global FSS scores and first order FSS scores were lower (r's
between .12 and .76) compared to previously noted correlations (Jackson
& Marsh, 1996).
Part II: Qualitative Analysis - interview Results. One purpose of
this study was to extend previous qualitative study (Jackson, 1995) of
factors that were relevant to helping, preventing, and disrupting flow
by examining collegiate athletes from team and individual sports. From
the inductive content analysis there were nine major dimensions
identified which were purported to help flow. These included; optimal
pre-competitive preparation plans, confidence & positive thinking,
optimal physical preparation, performance feeling good, focus, optimal
environmental conditions, positive coach/team interaction, optimal
pre-competitive arousal level, and motivated to perform. There were
eight major dimensions purported to prevent flow including; nonoptimal
confidence/positive thinking, nonoptimal physical preparation,
performing poorly, inappropriate focus, nonoptimal
environment/situation, negative/nonoptimal team interaction, overarousal
before competition, and lacking motivation. Finally, qualitative
responses from these athletes were grouped into six major dimensions
purported to disrupt flow. These dimensions included; putting pressure
on self and self-doubt, nonoptimal physical state, performance physical
state, performance errors, inappropriate focus, nonoptimal
environmental/situational influences, and problems with team
performance.
Factors Facilitating Flow
Nine dimensions were formed which represented factors helping this
sample of college athletes get into flow. There were 55 independent raw
data themes from the 42 interviews to answer what helped athletes get
into flow. A reliability checker independently classified raw data
themes into 16 higher order themes, and these themes into nine general
dimensions. There was 94% agreement at the raw data theme level, and
100% agreement at the higher order level. The six raw data themes which
were classified different from the investigator were discussed, three
were moved, two were re-worded, and the final theme was agreed to
maintain its original placement. Table 2 lists the raw data themes,
higher order themes, and general dimensions for factors helping flow.
For all dimensions discussed, the order is by percentage of athletes
represented.
Optimal Pre-competitive Preparation Plans. This dimension had the
largest percentage of college athletes citing a theme within it (52.4%)
and included 16.2% of all raw data themes. There were two higher order
themes that made up this dimension: optimal pre-competitive plans, and
being alone before competition. Thus, it appeared that for this sample,
being optimally prepared before their event was an important factor in
helping flow. Adherence to regular pre-performance mental preparation
routines, which often meant being isolated from others, was a salient
theme. For example, one athlete noted
I listen to music before a game. I always listen to the same tape
... I like to sit in the gym before each game by myself and picture
myself doing positive things on the floor. This mental rehearsal process
seemed to facilitate the enhancement of confidence as one-track athlete
indicated, by mentally going through my event, I am more confident in my
ability.
Optimal Physical Preparation. This dimension made up 48% of the
athletes and included 6.7% of all raw data themes, which were isolated
to one higher order theme of the same title. Being well prepared and
rested appeared to be related to one's mental preparation for this
sample. The following quote from a runner describes this relationship,
"Being well-rested and well-prepared as well as having a lot of
self-confidence helps me in my abilities."
Confidence and Positive Thinking. Thirty-three percent of the
athletes mentioned a theme related to this dimension, constituting 6.8%
of all raw themes. Three higher order themes were; confidence, positive
thinking, and enjoyment of the activity. Confidence was linked with
being able to eliminate ant negative thinking and focus solely on
positive performance attributes. For example, one volleyball player
indicated, "First, you have to have belief in yourself. You have to
have confidence in yourself you can build into a rhythm."
Optimal Arousal Level Prior to Competition. There was 29% of the
sample that indicated that optimal arousal levels were essential to flow
and this dimension represented 9.4% of all data themes. The higher order
themes of relaxation and getting energized to compete made up this
dimension. Similar to previous investigation of flow, certain athletes
mentioned that physical relaxation was more important to achieving flow,
while others favored inducement of increased arousal states to
facilitate flow (Jackson, 1995).
Performance Feeling Good. Nineteen percent of the participants
indicated that their performance during warm-up helped them to achieve
flow. Specifically, this dimension was composed of the higher order
theme warm-up feeling good, and contained 6.8% of all raw data themes.
Results from this dimension differed from previous flow findings
(Jackson, 1995) in that the higher order theme for this dimension was
limited to performance in warm-up. The underlying theme in this
dimension was that good physical preparation in warm-up was associated
with the necessary mental preparation that was a prerequisite for flow
states to occur.
Motivated to Perform. This dimension was related to having clearly
established goals and a sense of motivation to perform within the
athlete's event. Responses in this dimension made up 19% of all
athletes and represented 4.5% of all raw data themes. Two higher order
themes made up this dimension: clear goals and high motivation. These
two themes were linked because athlete were motivated as a function of
their pre-established goals and the importance of the given event.
Focus. For 17% of these athletes, good attentional focus was
important to getting into flow. This dimension represented 13.5% of all
raw data themes and consisted of the higher dimensions of good focus and
performance feels automatic. A theme among athletes in this dimension
was that one needed optimal focus in order to increase one's level
of performance. Effective focus seemed to be closely linked to
heightened self-confidence. One football player effectively summarized
this apparent association, "1 have to be focused and totally aware
of everything that is going on around me. This effects my confidence and
I feel like my senses go up a notch when I play well."
Optimal Environmental Conditions. This theme made up 14% of the
sample, and 4.1% of all raw data themes. This dimension was represented
by a single higher order theme of the same title. The type of event
played a role in how important environment was in helping achieve flow,
especially in duration events. For example, one runner mentioned that
temperature and scenery were important in longer races.
Positive Coach / Team Interaction. For 10% of the athletes,
positive coach and team interaction was cited as an antecedent to flow.
The higher order themes of positive coach feedback and positive team
interaction made up this dimension and represented 9.5% of all raw data
themes. While fewer athletes cited this dimension for helping flow, it
was evident for several team athletes, positive social support of
confident teammates and positive feedback from the coach prior to
performance were associated. For certain athletes, teammates appeared to
have an effect in optimizing pre-competitive arousal levels prior to
competition.
Factors Preventing Flow
There were eight dimensions inductively formed to represent the
factors that prevent athletes from getting into flow. There were 47
independent raw data themes elicited from the sample and a reliability
checker independently classified raw data themes into 21 higher order
themes, and higher order themes into the eight general dimensions. There
was 100% agreement at the raw data theme level, and 98% agreement at the
higher order theme level. A higher order theme (precompetitive
distraction) was moved to another dimension after discussing that it was
more appropriate with ideas in the dimension it was added (inappropriate
focus). Table 3 shows the raw data themes, higher order themes, and
general dimensions for factors preventing flow.
Non-Optimal Physical Preparation & Readiness. There were 48% of
the athletes that mentioned a theme in this dimension, which had the
highest percentage of athlete representation. There were five higher
order themes in this dimension, which made up 30% of all raw data
themes. Higher order themes for this factor were; not being physically
prepared, not feeling good physically, poor nutrition, and fatigue.
Obviously, in this dimension, when athlete did not feel optimally
prepared, their sense of readiness for competition and confidence about
performing well declined. While the focus was on non-optimal physical
factors, these were also related to psychological preparation factors.
For example, several athletes mentioned that a poor night's sleep
prior to competition negatively affected their physical readiness, but
this lack of sleep was due to worry over the upcoming competition.
Inappropriate Focus. This dimension, representing 40% of all
athletes, involved 25.3% of all raw themes and was comprised of the
higher order themes; poor concentration, losing focus, worry about
external factors, and precompetition distraction. In this dimension,
inappropriate focus was a function of inability to gate out distractions
or excessive rumination or concern over competitors. For some athletes
the inability to focus was related to outside stressors. As one swimmer
indicated, "If something happened that day to take my mind off the
meet, it's harder to concentrate on swimming. It takes total
focus." The other major theme was inappropriate attention focused
on opponents. One triathlete indicated focus problems when there were
many international competitors and a defensive player in football
indicated focus problems when the opposition's offensive linemen were physically larger in size.
Non-Optimal Environment / Situation. Twenty-one percent of athletes
interviewed referred to problems with nonoptimal environment or
situation as preventing flow. Higher order themes within this dimension
included non-optimal environmental conditions, external stress, dislike
for event, and situational stress, and represented 13.4% of all raw data
themes. Non-optimal conditions that influenced performance included
temperature extremes, poor weather, uncontrollable external stressors,
extensive travel and stress resulting from arguments with either a coach
or parent. In addition, one swimmer indicated that his dislike for a
particular distance event prevented him from achieving flow.
Non-Optimal Confidence / Positive Thinking. This dimension,
representing 17% of athletes' responses, was made up of non-optimal
confidence and negative thinking. These themes accounted for 10.4% of
all raw data themes. Clearly, to those athletes who reported this
response, non-optimal confidence levels were a factor in preventing
flow. Problems with confidence referred to both lack of confidence (as a
wrestler indicated), "If you go to the mat thinking you won't win", or as overconfidence (basketball player), "Cockiness can
prevent me from playing well."
Lacking Motivation to Perform. This dimension, representing 14% of
the athletes' responses and including 9% of all raw themes,
included low motivation and lack of challenge. Thus, one particular
aspect preventing flow appears to be a lack of skill-challenge balance
as proposed by Csikzentmihalyi (1990). This was evident by the following
comment from a basketball player, "It's hard to play when I
have a lack of motivation and I don't consider the game to be a big
deal."
Negative/Non-optimal Team Interaction. This dimension, involving
10% of athletes' responses, contained 5.97% of all raw data themes
and included the themes, negative team interaction and being isolated.
Individual differences were important within this dimension, in that two
athletes indicated that being around teammates with bad attitudes
prevented flow, while for two other athletes, being isolated from
teammates prevented flow.
Overarousal Before Competition. This dimension was unique from
other factors because it was specific to excessive anxiety as a theme.
Five percent of the athletes responses viewed excessive anxiety as
preventing flow and this dimension represented 2.99% of all raw data
themes. The two athletes who gave this response felt that if their
anxiety was too high, there was little they could do to intervene in
preparation to perform.
Performing Poorly. Five percent of the athletes cited performing
poorly as preventing flow, with the responses fitting specifically
within the title poor start and representing 2.99% of all raw themes.
For the two athletes expressing this theme, flow prevention factors were
unforced errors at the beginning of a game (basketball), and poor discus performance resulting in poor shot put performance (track and field).
Factors Disrupting Flow
Six dimensions were formed to represent factors that disrupt an
athlete once in flow state. Results are presented with the 13 higher
order and 46 raw themes from which they were developed. A reliability
check gave 94% agreement and the raw theme level and 100% at the higher
order level. One raw data theme was discussed and changed to a different
higher-order theme suggested by the checker. Table 4 shows the raw data
themes, higher order themes, and general dimensions for factors
disrupting flow.
Non-Optimal Environmental and Situational Influences. This
dimension had the most responses and consisted of 40% of all athletes
and 37% of all raw data themes. The higher order themes included in this
dimension were; mechanical failure, negative feedback from coach,
negative refereeing decision, what opponents are doing, stoppage in
play, and environmental distraction. Mechanical failure was relevant for
a triathlete (bicycle), and swimming (goggles). Negative coach feedback
was pertinent to team athletes distracted directly by the coach's
feedback, or discrepancies between their evaluation and the coach's
evaluation of performance. One basketball player felt that referees
disrupted flow "My game gets thrown off when the referees start
making bad calls and as a result I start missing baskets." In
addition, several athletes specifically indicated that opponents were
capable of disrupting flow. Runners were concerned about opponents'
pace, while football players were concerned with either opponent's
hard or i llegal hits. Three football players and one wrestler remarked
that stoppages in play had an effect on disrupting flow, which was
related to disruptions in concentration.
Performance Errors. Twenty-one percent of the athletes cited
performance errors as disrupting flow, which accounted for 19.6% of all
raw themes. All responses fit into one higher order theme by the same
title. Of the nine athletes who cited a theme within this dimension,
such occurrences as falls (track), turnovers and missed third down
conversions (football), missed moves (wrestling) and trying to do too
much in performance (baseball) represented various performance errors.
Inappropriate Focus. In addition to preventing flow, inappropriate
focus was mentioned by 21% of the athletes as disrupting flow and
accounted for 19.6% of all raw data themes. The two higher order themes
that made up this dimension were loss of focus and performance related
worry. Inappropriate focus took the form of simple loss of concentration
during the event, to having one's focus become occupied on the game
outcome. Excessive worry was also related to inappropriate focus, as
indicated by a volleyball player "I think a close scoring game
makes me feel pressured and I start worrying about what the coach is
thinking and that I can't screw up."
Non-Optimal Physical State. This dimension involving 17% of the
athletes and comprising 15.2% of all raw data themes, included one
higher order theme by the same title. The factors expressed within this
theme included disruptive effects of flow from physical injury, pain
during performance, and feelings of fatigue.
Putting Self-Pressure and Self-Doubt. Two athletes (5% of the
sample) expressed disruptions of flow within this dimension (4.3% of all
raw themes). Specifically, one baseball player felt his batting performance declined when he imposed increasing self-pressure and
another volleyball player felt disrupted when she began to
"second-guess" her performance.
Problems with Team Performance. Two athletes mentioned factors
within this dimension which accounted for 4.3% of all raw themes and had
a higher order theme of the same title. Responses within this dimension
related to disruptions due to teammates performance and when there was
the perception those teammates were not serious.
Perceived Controllability of Flow
In addition to being asked what factors helped, prevented, and
disrupted flow, athletes were also asked whether they perceived flow to
be controllable and rate each flow factor that was seen to
help/prevent/or disrupt flow on its controllability. Table 5 shows the
frequency of controllable versus uncontrollable flow factors. Overall,
64% of these athletes perceived flow to be a controllable state, while
36% said they felt that flow was uncontrollable. Several noted
quotations are mentioned below that provide insight with this particular
sample into the athletes' perceptions of flow controllability.
Certain athletes indicated that flow was a controllable state and
that getting into flow was a conscious process. One triathlete
indicated: I had total feelings of control over my body. I think you
control it when you ask your body to do it and it responds with high
energy. In addition, a baseball player indicated how flow was
controllable: It was a great feeling knowing that I had stood up to the
response and come through in the clutch. I had a feeling that I would
come through. I wanted the chance to hit. Several athletes mentioned
that flow was a controllable state to maintain, but achieving flow was
not within their control. This seemed to be a more salient theme with
team sport athletes than for individual sport athletes. For example, one
basketball player indicated this theme in the following quote:
Sometimes it depends on things that you can't control. One
game, the first time my guy took a shot I blocked it into the stands
then made a jump hook. From then on I was feelin' it. It was weird
because everyone around me seemed more sluggish and a gear behind me. I
felt like I was in cruise control and still in control.
Certain athletes also mentioned that their individual flow state
was more controllable than team performance and not always related to
team outcome, as one volleyball player indicated:
We played a good team and I think that affects ability to achieve
better performance. I remember running from spot to spot and it was fun
even though we lost. It was the most enjoyable time I had.
A larger percentage of this sample felt that flow was
uncontrollable than previous interviews (Jackson, 1995). Seventeen
athletes who were interviewed indicated they felt flow was not a
controllable state. These athletes indicated that it happened and one
could maximize its chances of occurrence but not guarantee its
occurrence. This was reflected by a comment football player's
comment:
I don't have control over whether or not I reach that state.
Every time you play you don't get there. You can be focused and not
in that state. But at the same time, if you want to get there, you have
to be focused.
In summary, this sample of college athletes indicated that while
the majority (64%) felt flow was controllable, a larger proportion felt
that flow was uncontrollable (36%), compared to elite athletes (79%)
(Jackson, 1995). Athletes indicated that while important factors were
controllable, the achievement of flow state was relatively less
controllable.
Discussion
This is the first study the author is aware of that has examined
flow experiences using the FSS across gender and sport settings as
potential independent variables to the flow experience and that has
combined the qualitative interview approach and quantitative assessment
of flow. The major purposes of this study were to (a) quantitatively
examine the variables of gender and sport setting and their potential
influence on flow factors, as measured by the Flow State Scale (Jackson
& Marsh, 1996) and (b) extend the qualitative findings of previous
flow study (Jackson, 1995, 1996) with less elite athletes. From the
qualitative interview data, nine dimensions were formed from raw data
themes about what helped athletes get into flow, eight dimensions about
factors preventing flow, and six dimensions about what disrupted the
flow process. There were considerably fewer total independent raw data
themes across these three factors (148) compared to Jackson's
(1995) sample (295) due to the fact that interviews were shor ter in
duration. Jackson (1996) has indicated that more experienced athletes,
by definition, have a larger reference base from which to draw upon when
thinking about flow experiences. These athletes, then, may have been
less proficient in recall of personal perceptions related to flow state.
Part I: Quantitative Results - Flow State Scale
Overall, the quantitative results from the flow state scale
assessment provide empirical support for the construct of flow for males
and females across team and individual sport settings. The
nonsignificant MANOVA results for gender and sport setting indicated
that college athletes experienced flow factors similarly, regardless of
gender or sport setting. Jackson and Marsh (1996) indicated that the
next step in examining the construct validity of the FSS was to examine
various methods of inferring flow with the same respondents. This study
examined flow both qualitatively and quantitatively with the same
athletes, and the FSS responses were analyzed in both a multivariate and
univariate fashion, to determine if gender or sport setting affected
isolated FSS factors. The only significant result from the separate
2-way ANOVAs of the nine FSS scores and total FSS scores was a
significant main effect for sport on action-awareness merging. With team
athletes reporting a significantly higher level of action-awarene ss
merging than individual sport athletes. Kimiecik & Stein (1992)
indicated the need to examine person and situation factors within flow.
These differences between team and individual sport athletes reflect
situational factors that may be pertinent in how athletes perceive flow.
The finding of greater action awareness merging in team athletes may be
attributed to the notion that for team sport athletes to perform at an
optimal level, they must have a sense that performance is automatic,
which is in turn related to better concentration levels. These aspects
of flow may not be less important in individual sports, but may be taken
for granted as necessary for effective individual sport performance, and
responses from individual athletes may have reflected this result
(Jackson, 1995). Such a conclusion is tenuous, because other situation
factors (self-paced versus other-dependent sports, open versus closed
skills) were not examined, yet may have influenced differences across
team and individual sports. In additi on, the same methodological and
conceptual problem exists for quantitative analysis of flow as
qualitative analysis of flow in that flow represents a process of
several factor operating together rather than in isolation. Therefore,
interpreting significant findings of FSS subscales may be empirically
undermining the construct of flow (Jackson, 1995, 1996).
Correlation coefficients between total FSS scores and FSS factors
support previous research indicating that the transformation of time
component may be less important than other factors in determining flow
(Jackson, 1996; Jackson & Marsh, 1996). However, in this study there
was also a lower correlation between total FSS scores and clear goals (r
= .21) indicating that for less elite athletes, clear goals may not be
as related to helping flow occurrence. It also seems apparent from the
correlation data that while there were moderate to high correlations
between FSS totals and FSS factors (r = .76 for paradox of control; r =
.70 for loss of self-consciousness), FSS results support Jackson and
Marsh's (1996) contention that FSS responses cannot be explained
very well by a single score or factor. Results also support that the FSS
may be useful with a more specific athletic sample (Jackson & Marsh,
1996). Future investigation of flow will need to incorporate
quantitative and qualitative methods in order to addres s the rich
content of the flow process, yet investigate systematic relationships
that may function as person (dispositional and state) and situational
factors that may influence the flow experience in sport (Kimiecik &
Stein, 1992). In general, the flow state scale results quantitatively
supported the qualitative interview results. Male and female college
athletes, across team and individual sport settings generally reported
no differences in the manner in which they experienced flow. Findings
from the current study extend the validity of the FSS in that
qualitative scores were related to qualitative content analysis of flow
occurrence in college athletes. Previous flow research (Jackson, 1995,
1996; Jackson & Marsh, 1996) by indicating that flow state can be
experienced by less elite athletes (Stein et al., 1995) and also that
less elite athletes have self-determination over flow, albeit
comparatively less than elite athletes (Jackson, 1995). This study also
supports the use of the flow state scale in assess ing factors related
to flow. The finding that there were no multivariate differences between
gender or sport setting on FSS scores indicates that flow factors are
generally experienced in a similar manner by males and female college
athletes across team and individual sport settings.
Part II: Qualitative Analysis Results
While there were some distinct differences in the current sample
from previous flow interviews (Jackson, 1995, 1996) there were also many
similarities from interview data. A discussion of each dimension
follows:
1. Confidence and positive thinking. Having elevated confidence was
a critical variable for achieving flow in these athletes and a closely
noted theme was one's ability to maintain positive thoughts to
facilitate confidence levels. Several athletes focused on their
perceived confidence, which reinforces the importance of this variable
in all levels of athletic performance (Jackson, 1995). This finding also
supports that confidence may be more related to the perception of
one's skills than to perception of challenge. These perceptions
were not as strong for dimensions reported within preventing or
disrupting flow.
2. Optimal Physical Preparation. This factor was relevant to all
three factors related to flow, similar to response from elite athletes
(Jackson, 1995). Obviously in order to achieve optimal performance, it
was necessary for athletes to have sufficient physical preparation.
Insufficient physical preparation was a salient issue when flow was
prevented and to a lesser extent, when it was disrupted. Specifically,
when flow was disrupted, it was more common for the result to be from
injury, excessive pain, or exhaustion. This finding reinforces earlier
findings on the importance of optimal physical states as a precursor to
flow (Jackson, 1995). Recently, Jackson et al., (1998) found that
cognitive anxiety was particularly strong in influencing state flow
measures. Since confidence may provide a buffer against the debilitative effects of anxiety, this supports the importance of high confidence in
facilitating flow.
3. Optimal arousal prior to performance. Athletes felt that
achieving an optimal precompetitive arousal level was necessary for flow
to occur. Two athletes mentioned that overarousal was a factor
preventing flow however, underarousal was not mentioned as problematic
by any athletes. Optimal arousal importance is well-documented in sport
psychology (Weinberg & Gould, 1999) and this factor of flow appears
to be associated with Hanin's (1992) individual zones of optimal
functioning theory, in that flow appears more likely if athletes have
achieved a pre-established optimal arousal zone prior to performance. By
having athletes predict precompetitive arousal levels within the IZOF
model (Hanin, 1989), coaches may be able to help athletes adjust
precompetitive arousal levels to maximize the flow occurrences.
4. How athletes' performance feels. When athletes perceive
their performance to be effective and feel good, they are much more
likely to achieve flow. Conversely, poor performance and errors are
factors in prevention and disruption of flow. From
Csikzentmihalyi's (1990) flow dimensions, when performance is
perceived as good, immediate and unambiguous feedback provides
information to the athlete regarding positive outcomes. When errors
occur, negative feedback is provided regarding athlete's
performance which raises self-doubt and preoccupation with outcome
rather than performance.
5. Motivated to perform. A high intrinsic motivation level stems
from athletes' perception of high skill-challenge balance
(Csikzentmihalyi, 1990) and was reported with these college athletes as
a factor in both helping and preventing flow. This factor supports the
importance of intrinsic motivation as a psychological correlate of flow
with less elite athletes (Jackson et al., 1998).
6. Appropriate Focus. This dimension has been referred to as one of
the most frequently mentioned flow dimensions (Csikzentmihalyi, 1990;
Jackson, 1995) and, for this sample, was reported with similar frequency
(17-40% of the time) compared to elite athletes' reports (Jackson,
1995). Within this sample, inappropriate focus was related to increases
in worry linked to self or others. This reinforces the finding that
attentional changes are closely associated with heightened competitive
anxiety (Martens, Vealey, & Burton, 1990)
7. Optimal environmental conditions. While this dimension was
reported across all three factors of flow, no optimal environmental
conditions had the largest impact on disrupting flow in this sample of
athletes, and was the single largest element in disrupting flow (40% of
the athletes reporting). Therefore, considering the performance
environment appears to be imperative for helping flow, and coaches and
athletes would appear to benefit from attentional refocusing strategies
and interventions prior to and during competition.
8. Positive coach/team interaction. Similar to Jackson's
(1995) interview results, this dimension was reported as relevant across
all three-flow factors. However, in this sample, coach interactions
appeared to have a more salient effect on helping, preventing, and
disrupting flow performance. This may have been due to a greater
reliance on coach feedback and interaction, since these athletes were
less-elite. Since recent research in team building (Ebbeck &
Gibbons, 1998) has shown to be effective as an intervention, the use of
team building to facilitate flow factors may be an area for future flow
investigation.
9. Optimal pre-competition preparation plan. In the current study,
this dimension contained the largest percentage of athletes reporting it
as important in achieving flow (52%). This finding was consistent with
Jackson's (1995) results (64% of athlete reporting this dimension)
and supports the importance of well prepared pre-competitive plans. This
finding also reinforces the importance of such mental training
interventions such as arousal regulation and mental imagery in preparing
for optimal performance.
Jackson (1995) found an experience factor as a dimension in helping
flow that was not observed in any themes within this set of athletes.
Thus, less elite athletes may not have sufficient experience to
replicate flow based upon previous flow experiences.
When results of these inductive analyses were compared with
previous work with elite athletes (Jackson, 1995, 1996) there was
considerable similarity in responses. All general dimensions for
helping, preventing, and disrupting flow found in elite athletes were
found in this sample, except for a reported experience factor in helping
flow and reported problems with pre-competitive preparation in
preventing flow. This study supported previous conclusions on the
importance of confidence and positive thinking in achieving flow
(Jackson, 1992, 1995). Jackson and Roberts (1992) reported that task
involvement and high-perceived ability were associated with frequency of
flow, and their results confirm the importance of perceived ability in
the confidence in an athletic context. Confidence and positive thinking
was less reported (38%) in the current sample compared with elite
athletes (64%), but was closely associated with other reported themes
(e.g. attentional focus). In addition, the salience of confidence as an
im portant theme supports findings that indicate a positive relationship
between flow and perceived ability (Jackson, 1995; Jackson &
Roberts, 1992; Jackson et al., 1998; Stein et al., 1995).
Perceived Controllability of Flow
One interesting finding from the qualitative analysis was the
percentages of college athletes who perceived flow as controllable. The
percentage of athletes reporting flow as a controllable state (64%) was
less than previously indicated by elite athletes (79%; Jackson, 1995).
Jackson (1995) reported that higher perceived controllability of flow
was invariably related to higher skill levels in elite athletes and the
overall percentage of perceived controllability of flow versus
uncontrollability in this study supports the notion that flow is
perceived as more controllable for elite versus non-elite populations.
Similar patterns emerged in this study compared to elite athletes
(Jackson, 1995) in that a majority of factors disrupting flow were seen
as uncontrollable.
One limitation of this study was that only two variables (gender
and sport type) were examined for their effect on FSS scores. A more
meaningful examination of flow factors may necessitate a more
comprehensive examination of both situational and personal factors and
their ability to predict flow occurrence (Kimiceik & Stein, 1992).
The correlations between FSS subscales and total FSS global scores
indicate that transformation of time may be a less pertinent factor in
flow occurrence and the low correlation for clear goals may have been
affected by the larger number of team sport athletes (28) compared to
individual sport athletes (14). For team athletes, individual goals may
be less relevant to individual flow occurrence compared to individual
sport athletes' performance (Kimiecik & Stein, 1992). Future
studies that examine flow should investigate less-elite athletes to
determine whether flow can be experienced in these populations. In
addition, future studies should continue to examine the complex nature
of flow by systematically comparing various methods of inferring flow.
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Flow State Scale Intercorrelations With Global Flow State Scale Scores
Intercorrelation Matrix Flow State Scale Subscales
Subscales #Chall Action Goals Feed Conc Cont Self Trans
Chall 1.0
Action .35 1.0
Goals .13 .61 1.0
Feed .16 .12 .17 1.0
Conc .04 .38 .02 .27 1.0
Cont .54 .44 .17 .21 .18 1.0
Self .38 .24 .10 .20 .02 .65 1.0
Trans -.22 .20 -.32 -.05 .08 -.001 -.15 1.0
Auto .14 .31 .04 .33 .19 .42 .39 -.02
Total .62 [*] .63 [*] .21 .45 [*] .41 [*] .76 [*] .70 [*] .12
Subscales Auto Total
Chall
Action
Goals
Feed
Conc
Cont
Self
Trans
Auto 1.0
Total .54 [*] 1.0
(*.)Correlations significant at p [less than] .005 level.
#Chall = Challenge-Skill Balance, Action = Action Awareness Merging,
Goal = Clear Goals, Feed = Unambiguous Feedback, Conc. = Concentration
on the Task at Hand, Cont. = Paradox of Control, Self = Loss of
self-consciousness, Trans. = Transformation of Time, Auto. = Autotelic
Experience, Total = Total Flow State Scale Score.
Factors Helping Flow
General Dimension Higher Order Theme
Optimal Precompetitive Plan Optimal Precompetitive Plan
Being Alone Before Competition
Confidence and Positive Thinking Confidence
Positive Thinking
Enjoyment of the activity
Optimal Physical Preparation Having Optimal Preparation
Optimal Precompetitive Arousal Relaxation
Getting energized to compete
Performance Feeling Good Warm-up feeling good
Motivated to Perform Clear goals
High motivation
Focus Good focus
General Dimension Raw Data Theme
Optimal Precompetitive Plan Being prepared mentally and physically
Being mentally prepared
Mentally preparing to remove anxiety
Game plan rehearsal
Mental rehearsal
precompetitive performance imagery (2)
Positive pre-game imagery
Consistent pre-game imagery (3 - 1
uncontrollable)
Being alone before my competition
Being alone before competition
Prefer to be by myself
Being alone before game (4)
Confidence and Positive Thinking Confident about opponent
Confident in ability to perform (2- 1
Uncontrollable)
Confidence (4)
Trust in my abilities
Confidence building before a game
Positive attitude
Positive self-image
Blocking out negative thoughts
Having fun
Enjoyment
Optimal Physical Preparation Knowing you're prepared through practice
Physically prepared for an event
Having prepared physically
Good pre-game nutrition
Being physically rested (2)
Optimal Precompetitive Arousal Being physically relaxed
Feeling excited before play
Getting energized before a game (2)
Getting oneself aroused before a game
Perfonnance Feeling Good Mentally/physically relaxed in warm-up
Physically feeling good in warm-up
Good physical pre-game warm-up
Vigorous physical warm-up (2)
Motivated to Perform Setting and accomplishing goals
Having a clear game plan
Motivated to play well for scouts
Focus Concentration
Good mental focus (3)
Lack of concern for competitors
Performance feels automatic
Optimal Environmental Environmental conditions
Conditions
Positive Coach/Team Positive coach feedback
Interaction
Positive team interaction
Not trying as hard
Performing skills automatically
Performance is automatic (3- 1 uncontrollable)
Optimal Environmental Start of the game
Conditions Good environmental conditions
Good awareness of the environment
Positive Coach/Team Positive feedback from coach
Interaction Receiving pep-talk from coach
Positive coach feedback in warm-up
Teammates getting pumped up
Positive interaction with team
Talking with teammates
Being around teammates
Notes. 1: Italics are factors which were uncontrollable.
2: Numbers in parentheses are number of athletes reporting.
Factors Preventing Flow
General Dimension Higher Order Theme
Nonoptimal Preparation / Not being physically prepared
Readiness
Injury
Not feeling good physically
Poor nutrition
Fatigue
Nonoptimal Environment Nonoptimal environmental conditions
or Situation
External stress
Dislike for event
Situational stress
Nonoptimal Confidence Nonoptimal confidence
Inappropriate Focus Poor concentration
Losing focus
Worry about external factors
Precompetitive distraction
Lacking Motivation Low motivation
to Perform
Lack of challenge
Overarousal Before Competition Excessive anxiety
Negative/Nonoptimal Team Negative team interaction
Interaction
Being isolated
Performing Poorly Poor start
General Dimension Raw Data Theme
Nonoptimal Preparation / Insufficient preparation (4)
Readiness Poor practices prior to competition
Becoming injured (2)
Physical illness (2)
Physical pain
Poor nutrition (2)
Poor night's sleep (2)
Feeling physically tired (3)
Being overtrained
Excessive travel to competition
Nonoptimal Environment Temperature extremes (2)
or Situation Poor weather conditions
External stress
Dislike for a particular event
Argument with parents
Negative feedback from others
Argument with coach (2)
Nonoptimal Confidence Lack of confidence (2)
Overconfidence
Negative attitude
Negative self-talk
Having negative thoughts
Negative imagery
Inappropriate Focus Inability to concentrate (2-1 uncontrollable)
Lack of concentration (2)
Being distracted by outside thoughts
(2-1 uncontrollable)
Not being focused on my race
Inability to eliminate distractions
Worry about competitors (3)
Worry about competing against somebody
better
Excess worry
Worry about a large crowd
Pre-race distractions
Distractions before competition
Lacking Motivation Lack of motivation
to Perform Low motivation (2)
Lack of concern over outcome
Opposition not a challenge (2)
Overarousal Before Competition Excessive anxiety (2)
Negative/Nonoptimal Team Teammates' bad attitudes
Interaction Focus distracted by teammates (2)
Not being around teammates
Performing Poorly Poor start (2)
Notes. (1.)Italics are uncontrollable factors.
(2.)Numbers in parentheses represent number of athletes responding
Factors Disrupting Flow
General Dimension Higher Order Theme
Nonoptimal Environment/Situation Mechanical failure
Negative feedback from coach
Negative referee decision
What opponents are doing
Stoppage in play
Environmental conditions
Nonoptimal Physical State Nonoptimal physical state
Problems with Team Performance Problems with team
Inappropriate Focus Los of focus
Performance-related worry
Performance Errors Performance errors
Putting Pressure nd Self-Doubt Putting pressure on oneself
Self-doubt
General Dimension Raw Data Theme
Nonoptimal Environment/Situation Equipment malfunction
Negative feedback from coach (2)
Coach removes me from game (2)
Poor calls by referees
Competitors influencing the race pace
Competitiors passing me
Getting hit hard by opponent
Illegal hit by opponent
Opponent's injury stops play
Stoppage in play (3)
Environmental disturbance
Crowd distraction
Distraction from specific person
Nonoptimal Physical State Physical injury (3-2 uncontrollable)
Feeling pain during performance
Feeling fatigued
Problems with Team Performance Team performing poorly
Teammates not serious
Inappropriate Focus Loss of concentration
Loss of focus (3 - 1 uncontrollable)
Start thinking about outcome (2)
Worry about what coach thinks
Worry about making mistakes
Worry about competitors performance
Performance Errors Not playing well (5 - 1 uncontrollable)
Performance errors
Falling during race
Overplaying/trying too much
Poor transition to different event
Putting Pressure nd Self-Doubt Putting pressure on oneself
Self-doubt
Notes. 1. Italics are uncontrollable.
2. Numbers in parentheses represent number of athletes responding.
Frequencies of Perceived Controllability
of Flow Fatcors
Factor Controllable Uncontrollable Total N
Help Flow 60(82.2%) 13(17.8%) 73
Prevent 38(58.5%) 27(41.5%) 65
Disrupt 19(42.2%) 26(57.8%) 45
Total N 117(63.9%) 66(36.1%) 183