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To the University of Wyoming:
The members of the Committee approve the thesis of Danilo Gomes de Arruda presented on
April 28, 2021.
Dr. Qin Zhu, Chairperson
Dr. Sean M. McCrea, Outside Member
Dr. Boyi Dai
Dr. Tucker Readdy
APPROVED:
Dr. Derek Smith, Division Chair, Kinesiology & Health Promotion
Dr. David Jones, College Dean, College of Health Sciences
1
Arruda, Danilo G., The effects of broken-down focus of attention instructions on volleyball
setting performance of skilled and novice players, M.S. Kinesiology & Health, May 2021.
Previous studies have shown advantage of external over internal focus of attention (FOA)
for motor learning and performance. However, the FOA effect became inconsistent when factors
such as task complexity, expertise, individual preference, and performance measurement are
considered. For complex motor skills like volleyball setting, broken-down FOA instructions are
often given to facilitate skill acquisition and performance, and it remained unknown whether
internal and external FOA instructions would impact performance of skilled and novice players
differently. Thirty-two novice (n=16) and skilled (n=16) players were asked to perform a
targeted volleyball setting task without (control) and with broken-down FOA instructions
(internal and external). Both movement outcomes and inter-joint coordination were analyzed.
The results supported previous literature on motor expertise showing that skilled players
outperformed novice players with superior movement outcomes due to their ability to maintain
an intermediate coordination pattern and functional variability of inter-joint coordination prior to
the ball contact. The FOA effect on inter-joint coordination was highly idiosyncratic with no
congruent pattern could be detected. Although FOA instructions reduced the variability of inter-
joint coordination for all players, it was detrimental for skilled players but beneficial for novice
players. Future studies should explore the effect of FOAs on motor coordination with a reduced
number of attentional cues in both internal and external formats, and the possibility of
participants switching between using internal and external cues for motor control.
THE EFFECTS OF BROKEN-DOWN FOCUS OF ATTENTION ON VOLLEYBALL
SETTING PERFORMANCE OF SKILLED AND NOVICE PLAYERS
By
Danilo Gomes de Arruda
A thesis submitted to the Division of Kinesiology and Health Promotion
and the University of Wyoming
in partial fulfillment of the requirements
for the degree of
MASTER OF SCIENCE
in
KINESIOLOGY AND EXERCISE SCIENCE
Laramie, Wyoming
May 2021
ii
ACKNOWLEDGMENTS
This research was only possible because awesome professionals and friends helped me
throughout the process. I want to thank Dr. Dai, who taught me how to properly collect and
analyze biomechanical data. I would also like to extend my gratitude to Dr. Readdy, who had
guided me with information about the graduate program since I started it. Many thanks to Dr.
McCrea, who promptly agreed to serve as a committee member and contribute to this research. I
also have to acknowledge the assistance of my friend Dr. Gylton Da Matta, who let me borrow
the equipment to do the research and always been willing to help and talk whenever I needed to.
I would like to express my deepest appreciation to my advisor, Dr. Zhu, who had shared with me
so much knowledge, expertise, and valuable pieces of advice, and given me autonomy and
encouragement for research, especially during the pandemic when things seemed to be out of
control. Finally, I want to mention my friends of SciTraining.com, Gustavo Api and Gabriel
Nappi. They have always been with me, supporting, chatting, and listening to my complaints
about how COVID delayed my research. I am really grateful.
iii
TABLE OF CONTENTS
Introduction ................................................................................................................................... 1
Literature Review ......................................................................................................................... 2
Attention ...................................................................................................................................... 2
Coordination ................................................................................................................................ 6
Volleyball Setting ...................................................................................................................... 11
Methods ........................................................................................................................................ 15
Participants ................................................................................................................................ 15
Instruments ................................................................................................................................ 15
Experimental Setup ................................................................................................................... 16
Procedure ................................................................................................................................... 17
Data Reduction .......................................................................................................................... 19
Setting Accuracy .................................................................................................................... 19
Motion Analysis .................................................................................................................... 20
I. 2D Motion Tracking ................................................................................................... 20
II. 3D Motion Tracking ................................................................................................... 21
Data Analysis ............................................................................................................................ 26
Results .......................................................................................................................................... 28
Compliance to FOA Instructions............................................................................................... 28
iv
Movement outcome ................................................................................................................... 29
Inter-Joint Coordination ............................................................................................................ 31
Variability of Inter-Joint Coordination ..................................................................................... 37
Discussion..................................................................................................................................... 41
Expert-Novice Difference ......................................................................................................... 41
FOA effect on Performance and Coordination ......................................................................... 44
FOA effect on Variability of Coordination ............................................................................... 47
Conclusion ................................................................................................................................... 50
Limitations of the study .............................................................................................................. 50
Practical implications ................................................................................................................. 51
Bibliography ................................................................................................................................ 53
v
TABLE OF FIGURES
Figure 1 - Four quadrants of Attentional Focus .............................................................................. 3
Figure 2 - CRP for recreational swimmers and competitive swimmers ......................................... 8
Figure 3 - Setting movement......................................................................................................... 12
Figure 4. Illustration of Experimental Setup ................................................................................. 17
Figure 5 - Scoring Rubric for Setting Accuracy ........................................................................... 20
Figure 6 - Camera View for 2D Motion Tracking ........................................................................ 21
Figure 7 - Global Reference Axes ................................................................................................ 22
Figure 8 - Unit vector and segment angle calculation .................................................................. 23
Figure 9 - View of the vectors for 3D Motion Tracking............................................................... 23
Figure 10 - Illustration of CRP Calculation .................................................................................. 24
Figure 11 - Coordination Profile of Elbow-Knee flexion/extension coupling ............................. 25
Figure 12 - Compliance to FOA Instructions ............................................................................... 28
Figure 13 - Mean Score of Setting Accuracy as a Function of Expertise and FOA ..................... 30
Figure 14 - Linear Regression on Max Ball Heights .................................................................... 31
Figure 15 - Mean CRPs of left and right elbow-knee couplings .................................................. 32
Figure 16 - Mean CRPs of Shoulder-Hip Girdle Rotation coupling ............................................ 33
Figure 17 - Mean CRPs of bilateral elbow coupling .................................................................... 34
Figure 18 - Individual FOA-specific CRPs of Right Elbow-Knee couplings ............................. 36
Figure 19 - Mean SD of CRPs ...................................................................................................... 37
1
INTRODUCTION
Volleyball is a popular sport with more than 800 million playing population worldwide
(Seminati & Minetti, 2013). Among many volleyball skills, the setting is a technically and
tactically important skill that decides the winning side of a game (Palao, 2018). Despite the
complexity of the involved multi-joint and full-body movements, volleyball setting is an
attention-demanding skill (Ozawa et al., 2019). The setter must direct the attention both
internally (to control body movement) and externally (to search for the task-relevant cues in the
environment) to decide when to initiate the setting, how to, and where to set the ball (Jóse
Afonso et al., 2009). The majority of studies on attention and performance showed more
advantages for external than internal focus of attention (Wulf et al., 2002). However, movement
outcomes associated with external cues have been traditionally used to quantify motor
performance and learning, which may have diminished the effect of the internal focus of
attention. In a cross-sectional study where experts and novices were compared, the effects of an
internal and external focus of attention seemed to vary depending on the motor expertise
(Perkins-Ceccato et al., 2003). Additionally, most of the investigations were conducted using
only simple tasks and discrete measurements, neglecting other important variables such as inter-
joint coordination and variability of movement.
The current study is aimed to examine the effects of internal and external FOA instructions on
volleyball setting performance of skilled and novice players. The general hypotheses are: 1)
skilled players should outperform novices in movement outcomes with different inter-joint
coordination pattern and functional variability; and 2) the effects of FOA instructions should
vary depending on the expertise.
2
LITERATURE REVIEW
Attention
Attention is a topic that has its roots in psychology in the 19th century. It can be
conceptualized in many ways, such as processing just one thing at a time or being selective
switching among multiple sources (Schmidt et al., 2019). The filter theories assume that one has
a fixed capacity of paying attention, and information processing can be overloaded when
multiple inputs demand attention and response simultaneously (Schmidt et al., 2019). Therefore,
the brain has to select and filter incoming information for processing; such a process is referred
to as "bottleneck" or selective attention (Wickens & McCarley, 2008). Using methods such as
self-reporting, eye movement recording, and cue occlusion technique (Abernethy & Zawi, 2007;
Lee, 2010; McPherson, 2000), researchers and practitioners have been trying to identify the
attentional cues that should be selected to facilitate motor performance and skill acquisition. To
be noted, most identified attentional cues are stimuli or events existing in the external world, and
few of them are related to the execution of body movement (Loffing et al., 2015).
Nideffer (1976) proposed an attentional model, stating that attention has two dimensions,
namely, the direction and breadth of focus. One can pay external-broad attention to assess the
environment in which the action is executed; external-narrow attention to act on the planned
3
actions; an internal-broad attention to analyze the opportunities for actions; and internal-narrow
attention to prepare for the planned actions (see Figure 1 below).
Figure 1 - Four quadrants of Attentional Focus (adapted from Nideffer, 1976)
As the sport skill becomes more complex and highly variable (E.g., open skills), it
requires an external focus. For example, a linebacker in football demanding a broad-external
focus or a tennis player demanding a narrow-external focus. Likewise, when the activities are
highly demanding on planning or analysis, an internal focus is required. For example, a
quarterback running a play strategy that relies on a broad-internal focus or a weight-lifter
demanding a narrow-internal focus (Nideffer, 1976).
Studies have been performed to investigate the effects of paying external or internal
attention on motor performance and skill acquisition (see a review by Wulf, 2013). Participants
were guided to pay attention to either internal cues (E.g., technique, body movements) or
external cues (E.g., environment cues, target) during execution or practice of motor skills, and
their retention performance was assessed and compared. The advantage of paying external
attention has been supported in that it typically resulted in better or more efficient motor
4
performance. Lohse, Sherwood, & Healy (2010) conducted an experiment to verify the
influences of the focus of attention (FOA) on dart-throwing in adult novice players. The
researchers measured throwing accuracy, kinematics, and muscle activation. The instructions
were given either inducing an external FOA (E.g., "mentally focus on the flight of the dart" p.
548) or internal FOA (E.g., "mentally focus on the movement of your arm" p. 548). The external
FOA group demonstrated a more accurate performance (less absolute error) and less muscle
activity in the triceps (the agonist muscle), with no difference found between groups for the
shoulder and elbow kinematics. Such superiority of the external FOA over the internal FOA has
been replicated in other sports skills such as pitching in baseball, snatch in weightlifting, driving
in golf, and free-throw in basketball (An et al., 2013; Lam et al., 2009; Oki et al., 2018; Schutts
et al., 2017). The Constrained Action Hypothesis (CAH) has been proposed to account for the
superiority of external over internal FOA in performance and acquisition of motor skills (Wulf et
al., 2001). According to CAH, consciously paying attention to the execution of movement (as
induced by the internal FOA) interferes with the automatic motor control processes that would
normally regulate the movement. Therefore, the attentional demand would be higher with
internal FOA and lower with external FOA, leading to the degraded performance in the former.
However, the superiority of external over internal FOA does not always hold as there has
been evidence showing the opposite or no difference between the two. Beilock and her
colleagues (2002) investigated soccer dribbling performance in novice and expert players and
found that the effects of attentional focus varied depending on the expertise. While the novice
players demonstrated the best scores using an internal FOA, the experts showed significantly
better performance under an external FOA. Interestingly, when the expert players executed the
trials using the non-dominant foot, they had the performance significantly increased by the
5
internal FOA, implying that the performance of novel movements could be enhanced by internal
FOA. Such a finding was corroborated by other studies using different motor skills (Castaneda &
Gray, 2007; Ford et al., 2005; Neumann et al., 2020; Petranek et al., 2019). Zentgraf and
Munzert (2009) hypothesized that the external FOA might be redundant and consequently
causing no change in kinematics, while the internal FOA could promote kinematics adaptations
challenging the learning. During the practice of juggling, participants were split into three
groups: the Control group did not receive any instruction, the External group was instructed to
focus on the ball flight, and the Internal group was instructed to focus on the arms movement.
The results showed that all groups improved performance (error and success rates) equally;
however, there was a significant difference for upper body kinematics and ball trajectories
between the Internal and External groups when they were performing juggling. More
interestingly, there was no difference in kinematics and ball trajectories between the External and
Control groups, suggesting that the instruction of paying attention to external cues was
redundant. As pointed out by some researchers (Beilock et al., 2002; Lazarraga, 2019; Petranek
et al., 2019), the internal FOA benefited the learners by directing their attention to the skill cues
directly relevant to movement, helping to develop and strengthen the basic mechanisms for
controlling movements, which is essential for learners at early stages of skill acquisition.
In conclusion, there is a controversy in determining whether the internal or external FOA
is more beneficial for motor performance and skill acquisition. Several factors seemed to mediate
the effects of FOA: The first two are the complexity of skill and expertise level. The external
FOA seemed to be more beneficial for simple and open motor skills, and for experienced and
skilled performers, because most relevant cues are external, and the automatic motor control
process needs no interference from the conscious internal FOA. On the other side, the internal
6
FOA seemed to be more beneficial for complex and closed motor skills, and for inexperienced
and novice performers, because most skill-relevant cues are internal, and the conscious attention
to the skill cues enhances the development of the representation of the motor skill. The third
factor is pertinent to performer's experience or preference of using attention cues. Maurer and
Munzer (2013) performed an experiment on skilled basketball players. They were asked to
identify the familiar and unfamiliar cues in both internal and external FOA categories before
performing free throws while focusing on one of four identified cues: familiar-internal,
unfamiliar-internal, familiar-external, and unfamiliar-external. The results showed that
performance decreased under both unfamiliar focus conditions, suggesting that the individual
experience (habit) of using attentional cues, independently of the direction of attention (internal
or external), determines the success of motor performance. The fourth factor is about
performance measurements. Most studies comparing the effects of internal FOA with that of
external FOA on motor performance have used discrete measurements on movement outcomes
(e.g., speed, accuracy), which often involved an object (e.g., target or sport instrument) that
demands external FOA. Such a discrete measure may inflate the effect of external FOA and
depreciate the effect of internal FOA because the measure that captures movement execution is
missing. Therefore, continuous measurements considering the ongoing interaction among body
segments are needed, and ideally be used together with discrete measurements to evaluate the
effects of both external and internal FOA on motor performance.
Coordination
Coordination can be defined as the capacity to control several movement possibilities
(degrees of freedom) by turning them into controllable units or synergies (Bernstein, 1996).
7
When one is learning a new motor skill, the brain is developing synergies to re-organize and
refine the muscle-joint linkages, consequently reducing the variability of inter-joint coordination
to guarantee the consistent production of superior movement outcomes (Chow et al., 2008).
Multiple methods have been used to quantify the inter-joint coordination, among which the
continuous relative phase (CRP) is the one based on the time series of angular speeds and
positions of two coupled joints. To obtain CRP, first, the phase angles (PA) of each joint are
calculated, which is the arctangent of the quotient between the angular speed and the angle of a
joint (Equation 1 - A). Then, the CRP (Equation 1 - B) is the difference between the PAs of the
coupled joints of interest. After normalization and removing redundancy, the final values of
CRP fall between 0° and 180° (Hamill et al., 1999), with 0◦ indicating the in-phase and 180◦
indicating the anti-phase coordination between the two joints.
Equation 1. A - Phase Angle() and B - Continuous Relative Phase() calculations. Where is the angular speed,
is the angle, and are the phase angles of the two coupling joints. The subscripts represent the data in
a given time.
CRP has been used to investigate a large spectrum of activities. Chiu and Chou (2012)
used CRP to examine the difference in gait pattern between young and elderly adults in response
to the change of walking speed, and found that young adults significantly changed the hip-knee
CRP pattern to adapt to the changing walking speed, which was not seen for the elderly adults.
Tavernese and colleagues (2016) used CRP to quantify the coordination between the pelvis and
the shoulder girdle during walking, and found that children with cerebral palsy demonstrated a
more in-phase pattern (CRP closer to 0◦) in the transverse plane than the typically developed
=tan1
=()()
8
children. Seifert and colleagues (2011) used elbow-knee CRP to capture the upper-lower limbs
coupling during a breaststroke cycle in swimming, and found that recreational swimmers
demonstrated a different upper-lower limbs coordination pattern that was also more variable than
competitive swimmers (as seen in Figure 2).
Figure 2 - CRP for recreational swimmers (left) and competitive swimmers (right) (Seifert et al., 2011).
According to the Haken-Kelso-Bunz (HKB) model (Kelso, 1984) developed to account
for coordinated movements, both in-phase (0°) or anti-phase (180°) coordination patterns are
stable (attractors) and fundamental. People are ready to perform either in-phase (e.g., jumping)
or anti-phase (e.g., walking) coordinated movements, but will need practice to learn any
coordinated movement that involves lagged coupling of joint movement (e.g., overarm
throwing). In motor skills involving multi-joint movement, the sequential kinematic chain is
often used to distinguish between skill levels (Mulloy et al., 2018), which stipulates that joint
movements should occur in a temporal sequence that promotes speed or force generation and
transfer among joints. Accordingly, novice performance, compared to expert performance, often
exhibits the in-phase coordination due to more time-locked movements among joints. Seifert et
al. (2010) examined the elbow-knee coupling pattern during a complete breaststroke cycle
between competitive and recreational swimmers. While the former showed a combination of
9
intermediate phase and in-phase knee-elbow coupling, the latter showed a mostly in-phase knee-
elbow coupling due to less time spent in the glide period of stroke. Similarly, Temprado et al.
(1997) examined the expert-novice difference in intra-joint coordination for the volleyball serve,
and the results showed that the dominant coordination pattern among shoulder, elbow, and wrist
of the serving arm was in-phase for novice players, while expert players maintained an anti-
phase coordination between shoulder and wrist throughout the serve. Recently, Sim et al. (2017)
compared the pelvis-thorax coordination patterns of professional and amateur golfers, and found
that the amateur golfers showed a more in-phase pattern throughout the whole movement, while
the professional players showed an anti-phase pattern during the transition from backswing to
downswing phase. To conclude, it seems that the intrinsic in-phase coordination pattern is
dominating the coordination in the early stages of skill acquisition before the task-specific (often
non-in-phase) coordination pattern is learned through practice (Huys et al., 2004).
The motor expertise can be revealed by not only the coordination pattern but also the
coordination variability. As a person gets more experienced with a motor task, a more consistent
use of task-specific coordination patterns should be expected. Chow and colleagues (2008) found
that as the participants improved their performance in a soccer kicking task, the variability of
inter-joint coordination in their kicking legs decreased. In well-controlled tasks and predictable
environments (closed-skills), experts are more likely to demonstrate more consistent
coordination than novices because the use of optimal coordination patterns developed through
practice is natural and efficient. However, when the task constraint or environment changed to
challenge flexibility and adaptability, experts often show more coordination variability than
novices. Such variability is functional because it allows the performer to adjust the body
movement to cope with the new demands rather than being inflexible or stereotyped. Studies on
10
elite triple-jumpers (Wilson et al., 2008) and race walkers (Cazzola et al., 2016; Preatoni et al.,
2010) have revealed that a high inter-joint coordination variability in the lower limbs is often
associated with expert performance that is deemed functionally better.
Along with motor expertise, FOA has been shown to affect motor coordination as well. In
fact, understanding how attention could influence motor coordination is a fundamental aspect of
comprehending the role of the central nervous system in motor control. Debaere et al. (2003)
reported that the cortico-cortical neuropathway was involved in performing a bimanual
coordination task when attention was directed externally to the visual cues, while the subcortico-
cortical neuropathway was involved in performing the same task when attention was directed
internally to the kinesthesis. Vidal and colleagues (Vidal et al., 2018) examined the lower limb
inter-joint coordination in standing long jump when college students were instructed to focus
either externally on a target or internally on the knee extension. The jumping distance was
greater with an external FOA. Regarding the inter-joint coordination, the participants showed an
in-phase pattern of ankle-knee coupling with external FOA, but a knee-dominating pattern with
internal FOA. According to the authors, the internal FOA constrained the automaticity of joint
coupling while the external FOA promoted it, supporting the constrained action hypothesis.
However, Komar et al. (2014) instructed novice swimmers to increase their stroke length in
breaststroke swimming with two attentional strategies. While one group received a specific
analogy directing attention to the outstretched arms, the other group was told to just focus on the
overall goal of the task (to increase the stroke length). The analysis of inter-limb coordination
showed that the analogy group increased the elbow-knee coupling with more time spent in the
anti-phase mode, while the external focus group remained to spend more time in the in-phase
mode, which was less efficient for the breaststroke. Thus, an internal FOA, specifically by virtue
11
of analogies, might direct the motor system to explore more efficient modes of coordination for
skill acquisition (Lam et al., 2009).
In sum, existing evidence seems to support the benefits of both internal and external
FOAs on motor coordination. However, motor expertise seems to be a confounding factor. As
novices are searching for the optimal coordination pattern to learn a motor skill, the internal FOA
would be beneficial because it promotes the specific movement exploration for implicit motor
learning (Liao & Masters, 2001). In contrast, experts may benefit from external FOA because it
promotes the automaticity of joint coupling that follows the acquired optimal coordination
pattern. As speculated by Peh et al. (2011), performers may alternate between different FOA at
different stages of learning. Therefore, to be effective, attentional instructions should vary
depending on motor expertise.
Volleyball Setting
Volleyball setting is a complex and attention-demanding skill (Ozawa et al., 2019). The
setters might direct attention to the players and the ball in order to decide where and how to set
the ball (Jóse Afonso et al., 2009). Since most points in volleyball come from attacks and the
setting precedes the action of attack, the quality of setting determines the efficiency of the
offensive system and, consequently, the victory in a match (Challoumas & Artemiou, 2018).
Different from the attacking skills (E.g., serving and spiking) that demand speed, the setting is a
skill that demands precise motor control of both upper and lower limbs to ensure the appropriate
ball contact and release. Despite the cognitive challenges to make a good decision about where
12
and how to set the ball, the execution of the setting technique also presents a biomechanical
challenge to the setter.
The most common setting technique is the overhead setting, in which the setter places
both hands over the forehead with the fingers spread, making a rounded shape to accommodate
the ball. As soon as the ball touches the hands, the fingers should briefly absorb the ball and push
it in the direction of the setting (see Figure 3).
Figure 3 - Setting movement (FIVB, 2017)
This is an elastic movement that highly demands a stretch-shortening cycle of wrist
flexor and the flexion/extension coordination between elbow and wrist (Ozawa et al., 2019). In
addition, lower limbs need to coordinate with upper limbs to locate the body underneath the ball
and then provide the foundation for a good execution of the elastic upper-limb movements. In an
early study, Ridgway and Wilkerson (1985) studied the kinematics of the front set performed by
collegiate female volleyball players. The research showed that the mean total time of ball contact
was 0.072±0.01 second, the ball's mean release velocity was 8.96±2.18 m/s with a mean release
angle at 62.01±5.04 degrees. At the ball release, the elbow flexed with a mean angle at
159.60±11.29 degrees, and the knee flexed with a mean angle at 150.51±15.63 degrees. The joint
13
range of motion was also measured for major joints of upper and lower limbs, which showed that
the shoulder, elbow, and knee moved with a much greater range than the wrist, hip, and ankle.
More recently, Ozawa and colleagues (2019) investigated the biomechanics of the upper-limbs in
the target-oriented overhead setting task. The subjects were male novice and expert volleyball
players. They found that the mean total time of ball contact was 0.087±0.023s, which was not
different between skill levels. The elbow flexion at the ball's contact was about 100° for experts
and 85° for novices, but at the ball's release, both groups had the elbow flexed at about 140°. For
both elbow and wrist motions, there was no significant difference between skill levels. However,
the expert players were found to maximize the angular speed of the elbow at 60-80% of the
normalized time before peaking the speed of the wrist at about 90% of the normalized time,
while the novice players peaked both elbow and wrist motions at around 90% of the normalized
time, suggesting that the kinetic chain was only used by experts.
The instructions about how to perform a volleyball setting can be found from various
sources, including federations' websites and coaches' manuals. They were developed based on
broken-down skill cues. According to the USA Volleyball Federation (USAV, 2020), the
execution of the volleyball setting should be as follows.
Here are a few things to keep in mind about setting:
1. Get to the ball.
2. Face your target (except when you're deliberately making a back set).
3. Bend your elbows and your knees.
4. Look at the ball through the opening between your hands.
5. Bring both hands into contact with the ball simultaneously.
6. Don't let the ball touch your palm. This is called a push, and is a violation. If the
ball comes to rest in you hand, or you strike the ball unevenly with either hand,
you'll be in violation.
7. Receive the ball over your head, and let it snap out of your finger pads. Keep your
hands above your face or you'll be whistled
14
Although the key skill cues are highlighted, the practical usage of this instruction is
limited due to the bi-foci on internal (E.g., hand, elbow, and knee movements) and external (E.g.,
ball and target) cues and the unnecessary sequential order of steps (E.g., one can look at the ball
and target at the same time while bending elbows and knees). In practice, coaches and athletes
often select the attentional cues based on their own experience and preference to teach and
practice the setting skill. However, it remains unknown whether the selected attentional cues are
actually effective in enhancing motor performance and promote motor learning.
Although studies have been performed to examine the effects of FOA on the motor
performance of volleyball serve and spiking (Alishah et al., 2017; Kountouris & Laios, 2007),
which showed advantages for external FOA, there has been a lack of study so far performed to
examine the effects of FOA on the motor performance of volleyball setting. The current study is
intended to fill this gap. Knowing that the effects of FOA on motor performance and
coordination may vary depending on the motor expertise, both skilled and novice players were
recruited to perform the setting under three instructions: control, internal FOA, and external
FOA. Knowing that the discrete movement outcome measures are more relevant to external FOA
and the continuous measure that captures the inter-joint coordination (E.g., CRP) is more specific
to internal FOA, both discrete and continuous measures were used to evaluate the effects of FOA
on the motor performance of volleyball setting. Based on previous literature, skilled players
should outperform novices in movement outcomes demonstrating task-appropriate inter-joint
coordination patterns with functional variability; and 2) the effects of an internal and external
focus of attention on both movement outcome and inter-joint coordination should vary
depending on the expertise.
15
METHODS
Participants
Based on the Power Analysis performed using G-Power (Ver 3.1.9), a minimum of 28
participants are required for a 2x3 (2 expertise levels by 3 FOA conditions) factorial design to
achieve a medium effect size (Cohen's f = 0.25) with a power of 0.8 (type I error) at a
significance level of 0.05. Accordingly, 32 participants were recruited from the University of
Wyoming community. Half of them (n=16) were skilled volleyball players (mean age of
20.25±1.39 years) with 6.8±2.3 seasons of training and competition experience. They maintained
the regular play or practice at least twice a week. The other half (n=16) were novice volleyball
players (mean age of 24.75±7.04 years) without previous formal training experience and regular
play. All participants gave their consent of participation before joining the study. The study was
approved by the University of Wyoming's institutional review board.
Instruments
Three high definitions (HD) video camcorders with a recording rate of 60Hz (JVC GC-
PX10; JVC, Tokyo, Japan) mounted on tripods (Ravelli AVTP Professional 65mm) were utilized
for motion capture. A three-dimensional direct linear transformation calibration frame (Peak
Performance; Englewood, CO, USA) was used for 3D data transformation. A meter ruler was
utilized for 2D calibration. A Tachikara SV5WSC volleyball (4.3 psi), a 2.3m high target stand
with a squared frame (0.75cm x 0.75cm) on its top, and a volleyball pitching machine (Tutor
Silver) were used for the targeted volleyball setting task. The instructions were given via audio
16
utilizing a set of stereo earphones (Model E138) connected to a laptop computer. For showing
the demonstration video, a 22inch computer screen was connected to a laptop playing the video.
Finally, colored adhesive tapes were used to identify the joints of interest for motion tracking.
Experimental Setup
The entire setup is illustrated in Figure 4. The participants performed the setting task in a
setting area, which was a square (1m x 1m) taped on the floor in front of the net and three meters
inside the court from the right sideline. Additionally, two cameras were positioned (6m apart
from one another) 7m away facing the participant with a 30° angle to the left and right. Another
camera was placed at the far end of the court on the extended midline, 14m perpendicular to the
ball motion plane. A target stand was utilized to assess setting accuracy. The target frame was
about 2.3m high (measured from the center of the target) and 20cm away from the net, tilting
towards the ceiling at 41°. It was positioned in front of the participants at a distance of 6m. The
pitching machine was placed about 7m away and in front of the participant at 45° to the left. The
position of the pitching machine was adjusted to make sure that the tossed ball could be set by
participants of different heights within the setting area. However, the pitching angle was set at
41°, pitching velocity at level 6, and the release height at 1.7m above the floor. Furthermore, a
tape of one meter long in length and 5 mm in width was placed on the floor (perpendicular to the
net and 3 meters away from the right-side line), creating an external visual cue in the setting
area, so in the external condition, the participant had to step over this line to do the set. On the
target, two colored tapes were adhered to the poles in parallel, one above the other (1.7 and 1.5m
from the floor), creating the external cue for lowering the eye height in the external condition.
17
Figure 4. Illustration of Experimental Setup
Procedure
The participants were briefed about the testing task in the beginning, and any questions
regarding the protocol were answered by the experimenter before they signed the consent form.
Participants and experimenters wore masks during the entire experiment to decrease the risk of
virus spreading (Covid-19). The experimenter verbally instructed the participants to place the
adhesive tapes on the joints of interest for motion capture. Specifically, the tapes were attached
to ankles (Lateral malleolus/Medial malleolus), knees (Femoral Epicondyles medialis/Lateralis),
hips (Greater trochanter), shoulders (Acromion), elbows (Humeral lateral epicondyle and medial
epicondyle), and wrists (Styloid process of radius and ulna).
Each participant was tested individually. The experiment started with a 5-min warm-up,
which consisted of a general warm-up (dynamic stretching and ball manipulation) and five
repetitions of the overhead setting task for familiarization. After the familiarization, an
instructional video from USA-Volleyball (https://www.youtube.com/watch?v=ckqFKsu-WIo)
18
was played to the participant to demonstrate the volleyball setting, highlighting the technique and
goal of the task. Subsequently, the participants were tested in three conditions. First, they were
tested in a control condition where no FOA was provided. Next, they were tested in either
internal or external FOA conditions. The order of each FOA condition was set counterbalanced
between the participants; that is, the order of FOA conditions switched for a new participant
every time.
Each FOA condition started with three warm-up setting trials, followed by five official
trials. In the Control condition, the participants performed the setting to a target without any
attentional instruction. In the following FOA conditions, the participants performed the task
directing their attention according to the given instructions. In the Internal FOA condition, the
participants were oriented to focus their attention on body movement. Whereas, in the External
FOA condition, the participants were oriented to only focus their attention on the target, ball, and
tapes on the floor. However, the same skill cues were used to develop both Internal and External
FOA instructions.
To ensure that the prescribed attentional focus instructions would be strictly followed, the
participants were asked to listen to the pre-recorded verbal instructions before each official trial,
and after each trial, they were asked to rate the extent to which they have followed the instruction
on each attentional cue by completing a questionnaire using a 5-point Likert scale. The specific
instructions and questionnaire can be viewed in Table 1.
19
Table 1: FOA Instructions and Questionnaires for Rating of Compliance to FOA instructions
INTERNAL
EXTERNAL
AUDIO FOA
INSTRUCTIONS
Remember to place the right foot forward,
bend your knees, and also to position your
fingers spread in front of the forehead,
forming a round shape. The thumbs and index
fingers should form a triangle. As you contact
the ball, be sure to extend both your arms and
legs in the direction of the intended set.
Finally, it is important to feel that your hands,
arms, and legs are moving elastically like a
spring.
Remember to take a step over the floor tape
and lower your eye height, allowing you to
see through the taped window formed by
Blue and Red tapes on the target while
searching for the ball. Once the ball is
located in the triangle formed by your raised
hands, reach to make contact with the ball as
high as possible, be sure to follow through in
direction to the target. Finally, try to find the
best ball trajectory to reach the target.
QUESTIONNAIRE
(Each to be rated 0-5 points)
Stepping forward with Right foot
Stepping crossing the line on the floor
Bending knees and arms
Lowering your eye height to see through
the taped window on the target
Placing hands in a round shape with the
thumbs and index fingers forming a
triangle in front and above your head
Locating the ball through the triangle
formed by your raised hands
Making contact with your hands above your
forehead and fully extending knees and
elbows
Reaching to make contact with the ball as
high as possible and then following through
in direction to the target
Data Reduction
Setting Accuracy
To quantify the setting accuracy, a scoring rubric was adopted (Figure 5). If the
participant made the ball pass through the target, 3 points were awarded. If the ball hit the target
frame, 2 points were awarded. If the ball touched any other parts of the target or passed through
the two support frames, 1 point was awarded, otherwise, 0 was awarded.
20
Figure 5 - Scoring Rubric for Setting Accuracy
Motion Analysis
All recorded video clips were manually digitized using MaxTRAQ, and X and Y
coordinates of the markers were submitted to Matlab 2016a routines for data analysis and
transformation. All data were digitally smoothed using a second-order low-pass Butterworth
filter with a cutoff frequency at 7Hz. This frequency was determined using the equation
suggested by Yu and Andrews (1998) designed to determine the optimal cutoff frequency based
on sampling frequencies.
I. 2D Motion Tracking
Camera three (Figure 4) was used to track the 2D motion of the ball. The center of the
ball was tracked (Figure 6), starting at the first frame that the participant's hands made contact
with the ball and ending at 20 frames after the peak ball height (Figure 6). The coordinates were
firstly converted to meters by scaling the data to a calibration device with a known distance of
one meter.
21
Figure 6 - Camera View for 2D Motion Tracking
The release velocity and angle of the ball were estimated using the first ten digitized
frames after the contact, among which the maximum resultant velocity was taken as the release
velocity and the angle of which (see Equation 2) as the release angle. The maximum ball height
was calculated as the maximum difference between the Y coordinate of the ball and the Y
coordinate of the reference point on the floor (Figure 6).
Equation 2 – Equation to determine the angle of release
II. 3D Motion Tracking
Camera one and two (Figure 4) were utilized to obtain the 3D coordinates of the joint markers for
examination of joint coupling. All joint markers were tracked in MaxTRAQ, starting at the frame when the
22
participant initiated the movement and ending at ten frames after the ball's release with the hands. For the joints
defined by two placed marking tapes (elbows, knees, and ankles), the point between the two markers was digitized.
In addition, the ball was digitized for the frames as it remained in contact with the participants' hands. This
digitizing allowed the determination of the ball contact window. Greater trochanter markers were further processed
to obtain the hip center point that was defined as 25% of the total distance between greater trochanters (Bennett et
al., 2016). Similar to the 2D analysis, the pixel coordinates were converted to meters. Subsequently, the data were
normalized to the individual movement duration to represent 0-100% cycle of the setting movement, which enabled
comparisons between subjects and trials. The direct linear transformation method was used to convert the 2D
coordinates from the two cameras into the 3D coordinates (X, Y, and Z). Three markers were placed on the floor to
obtain the global reference. X represented the axis perpendicular to the net, Y the axis parallel to the net, and Z the
axis perpendicular to the ground surface (up/downwards), as shown in Figure 7.
Figure 7 - Global Reference Axes
The interested inter-joint coordination patterns were lateral elbow-knee flexion/extension
coupling, shoulder-hip girdle rotation coupling, and bilateral elbow flexion/extension coupling.
The time series of elbow and knee flexion/extension and girdle rotation angles were calculated
using segment unit vectors. Specifically, the elbow angles were calculated using forearm and
upper arm vectors, the knee angles using the thigh and shank vectors, and finally, the rotations
using hip and shoulder bilateral markers in relation to the net (Figure 7). Each unit vector was
calculated using the coordinates of the marked joints according to the A-C steps listed below:
23
Figure 8 – Unit vector and segment angle calculation
The time series of girdle rotational angles was determined by calculating the rotational
angle of the girdle lines (connecting the two Acromions for Shoulder and connecting the two
Greater Trochanters for Hip) in the transverse plane with reference to the Y global reference
plane.
Figure 9 - View of the vectors for 3D Motion Tracking
The time series of angular velocities were calculated utilizing the first central difference
method. Also, to have the same amount of data points for speed, the forward difference method
Given Point A (X1, Y1, Z1) and Point B (X2, Y2, Z2):
A)
=12,12,12
B) ||
||=2+2+2
C) =
||
||
Then, a segment angle formed by two-unit vectors can be determined by the below steps:
Given Vector A (X1, Y1, Z1) and Vector B (X2, Y2, Z2)
1. A·B = X1*X2 + Y1*Y2 + Z1*Z2
2. |A|·|B| = (12+12+12 * (22+22+22
3. = (cos1A·B
|A|·|B | )(180
)
24
was utilized for the first data point, and for the last data point, the backward difference method
was utilized. The angles were expressed in degrees and the velocity in degrees per second.
Once the time series of both angle and angular velocity are obtained, the Continuous
Relative Phase (CRP) between joints and girdles can be calculated. Firstly, the angles and
angular velocities were normalized to -1 and 1 (see Equation 3 for the normalization procedure).
Secondly, the phase-angles of each joint or girdle were calculated by taking the arctangent of the
velocity divided by the angle (Panel A-B in Figure 9). Finally, the CPR is the absolute difference
between the two time series of phase angles (Panel C in Figure 9), which should fall between 0
and 180 degrees (Hamill 1999).
A-
B-
Equation 3 – A) segment angle normalization, where stands for the segment angle and for each data point within
the complete movement. B) angular velocity normalization, where is the angular velocity at each data point
Figure 10 – Illustration of CRP Calculation (adapted from Hamill et al., 2012)
25
According to Seifert and colleagues (2010), three coordination modes can be classified
based on the calculated CRP values: a CRP value that falls between 0 and 30 degrees is
considered as an in-phase dominant coordination mode and between 150 and 180 degrees, as an
anti-phase dominant coordination mode. For those that fall between 31 and 149 degrees, it is
considered as an intermediate coordination mode. Based on the frame of ball contact, the CRP
curve could also be analyzed separately to determine the coordination pattern in pre-contact and
post-contact phases. It turned out that the ball contact occurred the earliest at 81% among all
participants. Therefore, we defined 60% - 80% of the mean CRP curve as the pre-contact phase,
and 81% - 100% as the post-contact phase. Figure 10 illustrates the coordination profile of
Elbow-Knee flexion/extension coupling for an individual player in a setting trial with defined
coordination modes and pre- and post-contact phases.
Figure 11 – Coordination Profile of Elbow-Knee flexion/extension Coupling for an individual player in a setting trial
with defined coordination modes and pre- and post-contact phases.
26
Data Analysis
All dependent variables from data reduction were submitted to a series of ANOVAs and
time-series analyses to examine the effects of interest. The significance level was set to be 0.05
and partial eta squared (η2p) was calculated to quantify effect size. Also, all the analyses were
performed in R version 1.4.1106.
Compliance to FOA Instructions
To examine participants' compliance to FOA instructions, the self-rated questionnaire
scores were averaged across attentional cues in each FOA condition for each participant. A
mixed design 2-way ANOVA was performed to examine the effects of Expertise (Skilled vs.
Novice) and FOA condition (Control vs. Internal vs. External), as well as their interactions.
Movement Outcome
The movement outcome variables include scores of setting accuracy, angles and speeds
of ball release, maximum ball heights, and elbow flexion angles at the ball contact. A mixed-
design 2-way ANOVA was performed on all these variables, treating expertise (Skilled vs.
Novice) as a between-subject variable and FOA instruction (Control vs. Internal FOA vs.
External FOA) as a within-subject variable.
Inter-joint Coordination
Statistical Parametric Mapping (SPM) was used to analyze the time series of CRP data
(Pataky, 2010). Based on Random Field Theory (RFT), SPM estimates the significant difference
among CRP curves by computing a general linear model for each node (time point) across the
sample size, which creates a vector of regressors and error terms. Then, a map of those nodes can
27
be created through topological inference, and the probability of occurrence of significant
differences could be determined according to the interdependence and smoothness of data points.
SPM reduces the inflated type I error due to performing multiple t-tests at each individual node
in a time series (Pataky, 2010). Compared to traditional methods, SPM has advantages including:
1) the time series can be analyzed and interpreted in its full length; 2) It is possible to see the data
and easily identify the time stamps that the results were significant or not; 3) It allows the
utilization of common tests, such as ANOVA, which facilitates interpretation of the results and
application of the method in several domains (Serrien et al., 2019). The open-source Matlab
package (spm1d version M.0.4.7 @ www.spm1d.org) was used for SPM analysis. Specifically,
The SPM for two-way ANOVA was performed on the mean CRP curves to examine the effects
of expertise, FOA, and their interaction on the inter-joint coordination pattern. Additionally, we
also performed SPM for one-way repeated measure ANOVA for each individual participant to
see how the individual inter-joint coordination pattern would be impacted by FOA instructions.
The variability of inter-joint coordination was also examined to see how consistent
participants of different skill levels coordinated their body segments to set the ball with different
FOA instructions. Particularly, we were interested in the variability of inter-joint coordination
pre- and post- ball contact. Therefore, for a mean CRP curve calculated for 16 participants at the
same level who received a specific FOA instruction, the standard deviation (SD) from the mean
CRP was calculated at each data point in the pre-contact phase (60%-80%) and post-contact
phase (80%-100%). These SDs of CRP were then submitted to a 3-way ANOVA to examine the
effects of Expertise, FOA instruction, Phase, as well as their interactions.
28
RESULTS
Compliance to FOA Instructions
Overall, participants preferred the internal strategy more than the external strategy
(68.7% vs. 31.3% among skilled players and 50% vs. 31.3% among novices); however, three
novices preferred both strategies equally. When participants self-rated their compliance to FOA
instructions, novices rated 3.88 ±0.50 and 3.83±0.44 for internal and external FOA, respectively.
While skilled players rated the internal FOA as 4.27±0.42 and external FOA as 3.95±0.42,
respectively (see Figure 11). The two-way ANOVA showed a significant effect for Expertise (F1,
30 = 4.12, p = 0.05, η2p = 0.12), with skilled players rated themselves higher than novices in
adhering to the FOA instructions. However, a follow-up simple main effect analysis examining
the effect of FOA within each skill level revealed that skilled players perceived a higher
compliance to the Internal FOA than External FOA (F1, 30 = 5.79, p = 0.02, η2p = 0.16), while
novices perceived equal compliance to both FOA instructions.
Figure 12 – Compliance to FOA Instructions. The error bars represent standard error.
29
Movement outcome
The order of the FOA conditions was found to be insignificant (p < 0.05), thus was
removed from the analysis. The descriptive statistics of all movement outcome variables can be
seen in Table 2. The ANOVA yielded significant or marginal main effect for expertise on score
of setting accuracy (F1,30 = 104.63, p < 0.001, η2p = 0.78), release speed (F1,30 = 32.24, p < 0.001,
η2p = 0.52), max ball height (F1,30 = 8.96, p < 0.01, η2p = 0.23), and elbow flexion at contact (F1,30
= 3.88, p = 0.058, η2p = 0.11). There was no effect of FOA detected on any variable.
Table 2 Descriptive Statistics of Movement Outcome Variables in FOA conditions for Novice and Skilled players
with Main Effects of Expertise
Novices
Skilled
Main
Effect of
Expertise
F (1,30)
Control
Internal
External
Control
Internal
External
M
SD
M
SD
M
SD
M
SD
M
SD
M
SD
Setting Accuracy (0-5)
2.1
2
2.2
1.4
2.8
2.7
10.8
2.9
9.4
3.4
9.1
2.7
104.3**
Release Speed (m/s)
6.8
0.6
6.9
0.5
6.8
0.6
7.6
0.2
7.6
0.2
7.6
0.2
32.24**
Release Angle (°)
44.6
10.8
43.9
12.2
45
10.2
46.9
5.8
48.4
5.3
46.6
6.6
0.91
Maximum height (m)
3.3
0.5
3.3
0.6
3.3
0.6
3.7
0.3
3.8
0.3
3.7
0.3
8.96*
Elbow flexion Angle (°)
74.7
13.1
76.5
11.7
77.6
14.9
68
8
69.6
7.7
70.2
5.9
3.88*
** indicates p < 0.001
* indicates p ≤ 0.05
A marginal interaction between level and condition (F2,60 = 2.98, p = 0.058, η2p = 0.09)
was only detected for setting accuracy (see Figure 12). Therefore, simple main effect analysis
was performed to examine the FOA effect within each skill level. The results showed a
significant FOA effect for skilled players (F2,60 = 21.17, p < .001, η2p = 0.41), but not for novices
(p > 0.05). As revealed by a planned contrast, skilled players set the ball significantly less
30
accurate with internal (t (45) = 2.07, p = 0.04) or external FOA (t (45) = 2.43, p = 0.02) as
compared to the control condition, with no difference detected between the two FOA conditions.
Figure 13 – Mean Score of Setting Accuracy as a Function of Expertise and FOA. The error bars represent the standard
error. The letters represent a statistically significant difference detected by the planned contrasts analysis (p < 0.05).
Compared to skilled players, novices demonstrated a slower ball release with more flexed
elbow at contact, which resulted in a lower max ball height. To examine whether a more flexion
of the elbow at contact would result in a faster ball release and then a higher max ball height, we
regressed the max ball heights using ball release speeds and elbow flexion angles at contact,
separated for skilled and novice players. As seen in Figure 13, the linear regression was not
significant for skilled players, R2 = 0.02, F2,45 = 0.34, p = 0.71, but was significant for novices,
R2 = 0.60, F2,45 = 33.89, p < .0001, suggesting that a higher max ball height can be predicted
either by a faster ball release or a more flexed elbow at contact only for novices. As for skilled
players, there are other factors to determine the max ball height of their setting.
31
Figure 14 – Linear Regression on Max Ball Heights using Ball Release Speeds and Elbow Flexion Angles at Contact
for Skilled and Novice Players. The shaded areas represent the confidence interval from the linear regression.
Inter-Joint Coordination
Lateral Elbow-Knee Flexion/Extension Coupling. As seen in Panel A-D in Figure 14,
the mean CRPs in each FOA condition were plotted for novice and skilled players, separated for
left and right sides. In general, both sides demonstrated a shift from anti-phase to in-phase
coordination of elbow-knee flexion/extension before ball contact, and there was a quick change
to an intermediate coordination during contact before changing back to the in-phase coordination
in the end. It also seemed that FOA did not change such a coordination pattern for all
participants. However, there was a qualitative difference between novices and skilled players on
the left side in a portion of CRP right before the ball contact. These observations were confirmed
by SPM analysis with 2-way ANOVA. On the left side, the only difference was detected for the
32
factor of expertise (see Panel E in Figure 14), in which a cluster (p = .030) between 71% and
73% was found to be significantly above the threshold (F = 11.51), while no effect was found
significant on the right side (see Panel F in Figure 14).
Figure 15 - Mean CRPs of left and right elbow-knee couplings for novices (Panel A and B) and skilled participants
(panel C and D). The vertical dashed black lines represent the defined contact time (80%). The shaded blue area
represents in-phase coordination zone, and the pink shaded area at the top represents the anti-phase coordination zones.
The panels on the bottom (E and F) represent the SPM analysis using a 2x3 ANOVA showing the main effects of
Expertise, FOA, and their interaction. The red dashed lines represent the critical F-value threshold at the significance
level.
Shoulder-Hip Girdle Rotation Coupling. Figure 15 shows the CRP of shoulder-hip
girdle rotation coupling for novices and skilled participants (Panel A). Both groups demonstrated
a similar pattern, with the coordination being maintained at an intermediate mode (~60°). The
FOA conditions again failed to affect the joint coupling with no overt detection of separation
among the three CRP curves. As seen in Panel B in Figure 15, the SPM analysis did not reveal
D
C
B
A
E
F
33
any significant clusters (p > 0.05), suggesting that regardless of expertise and adopted attentional
strategy, participants coupled the shoulder and hip rotations in the same way to set the ball.
A
B
Figure 16 – Mean CRPs of Shoulder-Hip Girdle Rotation Coupling for novice and skilled participants (Panel A). Panel
B represents the SPM analysis using a 2x3 ANOVA showing the main effects of Expertise, FOA, and their interaction.
Bilateral Elbow Flexion/Extension Coupling. As seen in Panel A in Figure 16, the
bilateral elbow flexion and extension was, in general, maintained in an in-phase coordination
mode for all participants, regardless of the FOA conditions. However, skilled players seemed to
allow some intermediate coordination modes to occur in early (10-20%) and late (65-75%)
34
phases of setting, with a large variation of CRPs. As revealed by the SPM analysis with 2-way
ANOVA (Panel B in Figure 16), there was a marginal main effect of expertise for a node at 68%
with the maximum F value of 11.61, nearly reaching the threshold (F = 12.08) at the significance
level. The effects of FOA and FOA by Expertise interaction were not detected.
A
B
Figure 17 - Mean CRPs of bilateral elbow coupling for novices (Panel A) and skilled (Panel B) participants. The panel
at the bottom (B) represents the SPM analysis using a 2x3 ANOVA showing the main effects and interaction.
35
FOA Effect on Individual Coordination. Since the FOA effect was not found to affect
all interested inter-joint couplings when CRPs were averaged across the expertise group and
FOA conditions, we wondered whether there was a high individual difference for FOA to affect
the inter-joint coordination at different phases of coordination. Therefore, we plotted the three
mean CRP curves to represent the FOA-specific coordination patterns for each participant, and
then performed SPM analysis with one-way repeated measure ANOVA to examine the FOA
effect on each coordination pattern of interest. The results confirmed our hypothesis showing that
FOA impacted the inter-joint coordination with high individual differences. Figure 17 illustrates
the FOA-specific CRPs of Elbow-Knee Flexion/Extension on the right side for three individual
players from each expertise group, with the results of SPM analysis. The first row shows the
significant FOA effect in the early phase of coordination for both skilled (Participant AC) and
novice (Participant RC) players, the second row shows the significant FOA effect in the middle
phase of coordination for both skilled (Participant EE) and novice (Participant XW) players, and
the last row shows no FOA effect at all for both skilled (Participant CT) and novice (Participant
AT) players. In addition, the CRP curves were not consistent in shape among players of the same
skill level. Therefore, the FOA effect on inter-joint coordination is individually unique, and no
consistent conclusion can be drawn for a group of players even if they are in the same skill level.
36
Figure 18 – Individual FOA-specific CRPs of Right Elbow-Knee Couplings for three Skilled (left column) and Three
novice participants (right column). The plots underneath CRPs represent the results of SPM analysis with one-way
repeated measures ANOVA. The red dashed lines represent the critical F-value threshold at the significance level.
37
Variability of Inter-Joint Coordination
As seen in Figure 18 (Panel A-D), the mean SDs of CRPs for all interested coordination
were plotted as a function of Expertise, Contact Phase, and FOA. It seemed that the mean SDs
varied among FOA and between contact phases depending on the expertise level. The 3-way
ANOVA revealed significant 3-way interactions (F2,76 ≥ 4.14, p < 0.05, η2p ≥ 0.1) on all
interested coordination, therefore, a 2-way ANOVA treating both contact phase and FOA as
within-subject factors was performed separately for skilled and novice players to examine how
the variability of coordination changed before and after ball contact under the influence of
different FOAs.
Figure 19 – Mean SD of CRPs as a Function of Expertise, Phase, and FOA for Left Elbow-Knee Coupling (Panel A),
Right Elbow-Knee Coupling (Panel B), Shoulder-Hip Girdle Rotation Coupling (Panel C), and Bilateral Elbow
Coupling (Panel D).
38
For variability of left Elbow-Knee coupling (Panel A in Figure 18), the 2-way ANOVA
showed significant main effects for contact phase (F1,19 = 131.59, p < 0.0001, η2p = 0.87) and
FOA (F2,38 = 12.43, p < 0.0001, η2p = 0.40) without interaction for skilled players, but both
significant main effects (F1,19 = 38.01, p < 0.0001, η2p = 0.67 for contact phase; F2,38 = 10.11, p <
0.0001, η2p = 0.35 for FOA) and interaction (F2,38 = 24.64, p < 0.0001, η2p = 0.56) for novice
players. The planned contrast analysis showed that only the external FOA resulted in a reduced
variability of coordination from control (t (38) = 3.51, p = 0.001) for skilled players. The simple
main effect analysis also revealed a significant FOA effect in pre-contact phase for novice
players (F2,76 = 27.44, p < 0.0001, η2p = 0.42), and the following planned contrast showed that the
coordination was significantly less variable with external FOA as compared to the control (t (76)
= 7.05, p < 0.001) and internal FOA (t (76) = 5.48, p < 0.001), with no difference detected for the
latter two (t (76) = 1.57, p = 0.12).
For variability of right Elbow-Knee coupling (Panel B in Figure 18), the 2-way ANOVA
showed significant main effects for contact phase (F1,19 = 170.41, p < 0.0001, η2p = 0.90) and
FOA (F2,38 = 11.76, p < 0.0001, η2p = 0.38) without interaction for skilled players, but significant
main effect for FOA (F2,38 = 10.85, p < 0.0001, η2p = 0.36) and FOA by contact phase interaction
(F2,38 = 3.53, p < 0.05, η2p = 0.16) for novice players. The planned contrast showed that the
internal FOA resulted in a reduced variability of coordination from control (t (38) = 2.93, p =
0.006) and external FOA conditions (t (38) = 3.006, p = 0.005) without the difference between
the latter two for skilled players. The simple main effect analysis also revealed a significant FOA
effect in post-contact phase for novice players (F2,76 = 11.47, p < 0.0001, η2p = 0.23 ), and the
following planned contrast showed that their coordination was significantly less variable with
39
both internal and external FOA (t (76) = 4.6, p < 0.0001 for internal FOA, t (76) = 3.44, p =
0.001 for external FOA) as compared to the control post the ball contact.
For variability of Shoulder-Hip rotation coupling (Panel C in Figure 18), the 2-way
ANOVA showed significant main effects for contact phase (F1,19 = 33.76, p < 0.0001, η2p = 0.64)
and FOA (F2,38 = 9.16, p < 0.01, η2p = 0.33) with a significant interaction (F2,38 = 68.20, p <
0.0001, η2p = 0.78) for skilled players. As for the novice players, the main effects and interaction
were also significant (F1,19 = 60.30, p < 0.0001, η2p = 0.76 for contact phase; F2,38 = 8.16, p <
0.01, η2p = 0.30 for FOA; F2,38 = 4.66, p < 0.05, η2p = 0.20 for interaction). The simple main
effect analyses revealed that the FOA effect was significant in both contact phases for both
skilled (F2,76 = 46.70, p < 0.0001, η2p = 0.55 in pre-contact; F2,76 = 5.54, p < 0.01, η2p = 0.12 in
post-contact) and novice (F2,76 = 5.05, p < 0.01, η2p = 0.11 in pre-contact; F2,76 = 9.20, p <
0.0001, η2p = 0.19 in post-contact) players. As revealed by the following planned contrasts: for
skilled players, both internal and external FOA significantly reduced the variability of
coordination from control (t(76) = 7.96, p < 0.0001 for internal FOA; t (76) = 8.72, p < 0.0001,
for external FOA) before the ball contact, but only external FOA significantly increased the
variability of coordination from control (t (76) = 3.27, p = 0.002) post the ball contact; then for
novice players, only the external FOA significantly increased the variability of coordination from
control (t(76) = 2.49, p = 0.01) before the ball contact, while only the internal FOA significantly
reduced the variability of coordination from control (t(76) = 3.64, p < 0.0001) post the ball
contact.
For variability of bilateral elbow coupling (Panel D in Figure 18), the 2-way ANOVA
showed significant main effects for contact phase (F1,19 = 87.27, p < 0.0001, η2p = 0.82) and FOA
(F2,38 = 9.68, p < 0.0001, η2p = 0.34) with a significant interaction (F2,38 = 3.68, p < 0.05, η2p =
40
0.16) for skilled players. As for the novice players, the main effects and interaction were also
significant (F1,19 = 93.24, p < 0.0001, η2p = 0.83 for contact phase; F2,38 = 35.42, p < 0.0001, η2p =
0.65 for FOA; F2,38 = 6.41, p < 0.01, η2p = 0.25 for interaction). The simple main effect analyses
revealed that the FOA effect was significant in both contact phases for both skilled (F2,76 = 9.96,
p < 0.0001, η2p = 0.20 in pre-contact; F2,76 = 4.97, p < 0.01, η2p = 0.12 in post-contact) and novice
(F2,76 = 23.71, p < 0.0001, η2p = 0.38 in pre-contact; F2,76 = 3.60, p < 0.05, η2p = 0.09 in post-
contact) players. As revealed by the following planned contrasts: for skilled players, only the
external FOA significantly reduced the variability of coordination from control before (t (76) =
3.28, p = 0.002) and after (t(76) = 3.13, p = 0.002) the ball contact; then for novice players, both
internal and external FOAs significantly reduced the variability of coordination from control (t
(76) = 4.28, p < 0.0001 for internal FOA, and t (76) = 6.80, p < 0.0001 for external FOA) before
the ball contact, while only the internal FOA significantly reduced the variability of coordination
from control ( t(76) = 2.61, p = 0.01) post the ball contact.
41
DISCUSSION
Although the literature (Wulf, 2013) has suggested a superiority of external over internal
FOA for motor learning and performance, the effect became inconsistent when factors such as
task complexity, expertise, individual preference, and performance measurement were
considered. Using both outcome and kinematic measures, the current study investigated the
effect of FOA on motor performance of volleyball setting performed by skilled and novice
players. We hypothesized that both performance and FOA effect would differ between skilled
and novice players. The results showed that skilled players outperformed novices with a higher
setting accuracy, a higher max setting height, a faster ball release, and a more extended elbow at
ball contact. However, the FOA instructions negatively affected the setting accuracy of skilled
players with no difference between internal and external FOAs. Although FOA instructions
failed to affect the mean inter-joint coordination patterns due to the high individual difference
detected for FOA effect among both skilled and novice players, it was remarkable to see that
FOA instructions impacted the variability of inter-joint coordination before and after the ball
contact, which meant differently for skilled and novice players.
Expert-Novice Difference
As expected, skilled players outperformed novice players in most outcome measures due
to their well-developed technique and advanced perceptual-motor system (Davids et al., 2015).
Setting is determinant for the offensive system in volleyball as a good setting will allow the
attacker to hit more efficiently and score more points (González-Silva et al., 2020). In a good
setting, the ball is delivered accurately to the position near the net where the spiking occurs (a
42
higher accuracy), which should also be supported by a higher setting height that allows the time
for the attacker to perform a jump to spike. In addition, the faster ball release with a more
extended arm at the ball contact would increase the consistency of movement, disguising the
direction of setting. These results are in accordance with previous studies on setting
biomechanics of skilled female players (Maessen & Holt, 1986; Ridgway & Wilkerson, 1985). It
is also likely that skilled volleyball players have developed optimal kinetic chain for setting
because a more extended arm at release has been an indicator for better utilization of a kinetic
chain in striking and throwing skills (Kibler & Sciascia, 2004).
The optimal performance can be revealed by correlating among performance variables
rather than analyzing one single variable at a time (Thompson et al., 2000). When the max
setting heights were regressed using release speeds of the ball and elbow flexion angles at the
ball contact, only novice players showed a significant correlation, in which either a faster ball
release or a more flexed elbow at the ball contact could predict a higher setting. This indicates
that novice players heavily relied on the elbow flexion and extension to set the ball faster and
higher. In contrast, skilled players did not show any significant correlation, suggesting that the
ball height of skilled setting was not determined solely by the release speed or elbow flexion and
extension before contact, rather, it could be a result of simultaneous manipulation of multiple
variables including upper-lower limbs coordination, fingers flexion and extension, and release
parameters by skilled players. Such a high degree of freedom in manipulating the sequential
action elements has been shown to facilitate goal-oriented joint movements (Herbort & Butz,
2012).
The expertise effect was also found in the analysis of inter-joint coordination patterns.
The SPM ANOVAs yielded a significant difference between skilled and novice players on the
43
left-side elbow-knee coupling and bilateral elbow coupling, both in the pre-contact phase. While
novice players demonstrated an in-phase dominant coordination, skilled players exhibited an
intermediate coordination pattern, suggesting that the flexion and extension between elbow and
knee on the left side and between both elbows are not completely locked/synched for the skilled
setting. Sefeirt and colleagues (2010) found a similar result in comparing the elbow-knee
coordination between skilled and novice swimmers. In general, the novice swimmers spent more
time in an in-phase coordination mode than skilled swimmers. According to Kelso (1984), the in-
phase coordination is the most stable coordination pattern that can be produced without practice
and maintained at high frequency. As hypothesized by Berstein (1967) and then evidenced by
many studies (Chow et al., 2008; Gray, 2020), in early skill acquisition, novices rely more on the
basic coordination patterns to perform the task, and they also tend to freeze degrees of freedom
among joints to allow for an easier motor control, which typically results in the rigid and in-
phase dominant movements. However, skilled performance is often featured with decoupling
movements among joints, so-called kinetic chains as seen in skilled striking or throwing tasks
(Naito et al., 2017; Temprado et al., 1997). Particularly, some level of decoupling among joints
before the object contact would be necessary for interceptive tasks, because it would allow for
final adjustment of action components to ensure the accurate interception with the object. In the
setting task of the current study, more adjustment was needed on the left side than right side
because participants turned to receive the ball coming from the front left by stepping forward
with the right foot, which means the left elbow and knee were responsible for not only pushing
the ball up but initiating the body rotation toward the target. Consequently, the intermediate
coordination pattern in coupling left elbow-knee and bilateral elbow flexion-extension
movements prior to ball contact is expected for skilled setting.
44
The adjustment of inter-joint coordination prior to the ball contact was further supported by the
finding that skilled players demonstrated a consistently higher variability of coordination than
novice players in the pre-contact phase (see Figure 18). Specifically, for elbow-knee and bilateral
elbow couplings, skilled players showed a greater variability in the pre-contact phase followed
by a significant reduction of variability in the post-contact phase, while novice players did not
show the same with a comparable magnitude. The high variability of coordination is considered
to be functional as it allows for efficient movement adjustments (Davids et al., 2006). Numerous
studies have shown that skilled performers increase variability of movements to facilitate the
search for the optimal movement solution, which yielded a superior performance (Barris et al.,
2014; Seifert et al., 2014; Wilson et al., 2008). Since volleyball setting is an open sport skill,
allowing the inter-joint coordination to vary with a high degree of freedom up to the ball contact
is a functional strategy for players to deal with the ever-changing environment and produce a
setting optimal to the situation at the moment.
FOA effect on Performance and Coordination
Regarding the FOA effect, skilled players showed a decreased setting accuracy than
control with either internal or external FOA instruction. The negative effect of FOA on skilled
performance has been documented in earlier research as well. Wulf (2008) reported that expert
acrobats decreased the frequency of movement adjustments in a balance task with either internal
or external FOA strategy, which was unnatural to them. Similarly, Malek et al. (2012) found that
paying attention either to the racket or arm movement deteriorated serving performance for
skilled badminton players. Therefore, at higher level of expertise, any added or imposed
attentional demands might be detrimental to performance due to its hindrance to movement
45
automaticity (Wulf, 2013). This is also referred to as choking, which is a deteriorated
performance due to over concerning about the quality of movement or movement outcomes
(Moran, 2012). It seems that skilled performance is supported by automatic attention that does
not disrupt the movement automaticity, rather than controlled attention that imposes the attention
to either internal or external cues (Castaneda & Gray, 2007). Skilled players preferred internal
than external FOA in our study because the broken-down internal cues were more consistent
with their knowledge base, while the broken-down external cues were somewhat unnatural to
them. For instance, Sibley and Etnier (2004) reported that attention to the ball was highly
demanded in the early and late flight of the ball for skilled volleyball setters, therefore, the
instructions of peeking at the floor and looking through the taped window to ensure the forward
stepping and knee bending would be distracting or redundant since they could be easily taken
care of by the peripheral vision, instead of focal vision. In fact, the eye-tracking and self-
reporting data from an in situ volleyball study (Afonso et al., 2009) revealed that skilled players
spent more time focusing on the potential attackers and opponents while they tracked the ball
movement.
The novice players in our study did not show any improved performance (a higher setting
accuracy, a higher setting height, a faster ball release, and a more extended elbow at contact)
with either FOA instruction, which was contradictory to the previous finding that the internal
FOA was beneficial for novices (Lazarraga, 2019; Wulf, 2013). Compared to previous studies,
the number of internal or external provided cues (four vs. one) was significantly higher, which
might have elevated the amount of information processing to overload novice players while they
were already asked to perform a challenging task. In fact, most novice participants had trouble in
focusing on the provided cues based on their feedback after the experiment, and their self-rated
46
compliance to FOA instructions was also lower than skilled players. In a recent study by
Raisbeck and Diekfuss (2017) the number of cues was manipulated for both internal and external
FOA, and the results showed that the performance of using one cue was superior to that of using
three cues in both FOA conditions, although the external FOA remained to be more beneficial
than internal FOA for performance. Despite the consistently poor performance with and without
FOA instructions, novice players preferred internal FOA more than external FOA, suggesting
that the broken-down internal cues were perceived to be more useful for novice players. Landin
(1994) has recommended that verbal cues must be unambiguous to promote skill acquisition.
Compared to the internal cues that precisely defined the procedure of body movement, the
external cues were vaguely defined and requiring the player to figure out the relationship
between the cues and body movement. Without knowing the required movements corresponding
to those external cues, novice players could be confused by being asked to constantly shift
attention among those cues.
When FOA effect was examined on the mean coordination pattern of inter-joint
couplings for both skilled and novice players, we did not see that internal or external FOA
changed the coordination pattern significantly from the control at all. However, the following
examination of FOA effect on individual coordination pattern of inter-joint couplings revealed
that FOA affected the individual coordination pattern with a high individual difference: the effect
was found significant either in the early or middle phase of setting, or completely absent during
the entire phase of setting. Sarvestan and colleagues (2020) investigated the coordination pattern
of hitting movement in elite volleyball players using the method of self-organizing maps, and no
systematic similarity of coordination pattern was found in that each player demonstrated a
unique pattern. In our study, each participant may have perceived and responded to the FOA
47
instructions differently, therefore, different strategies may have been implemented to coordinate
the joints, which led to the inconclusive FOA effect on inter-joint coordination. A recent study
(Popp et al., 2020) even suggested that initial instruction with different ways of breaking down a
skill could lead to better or worse initial performance, however, individual learners were capable
of reorganizing and chunking the instructional cues in different ways to achieve the same level of
learning in the end.
As for why internal FOA did not differ from external FOA to impact inter-joint
coordination and movement outcomes. The same skill cues were used to develop FOA strategies
that were only different in the direction of attention, consequently, participants could interpret
different cues as the same through common coding (Poolton et al., 2006), which resulted in the
same strategy used for motor control. A previous study (Post et al., 2011) showed that
participants might not strictly comply to the FOA instructions and often switched between using
internal and external cues. One cannot avoid the external cue that is inherent to the task (E.g.,
visually tracking the ball in playing volleyball) even when internal FOA is given. Thus, the
attentional strategy for executing motor skills might be more complex involving switching
between internal and external cues (Peh et al., 2011).
FOA effect on Variability of Coordination
The novel finding of the current study is the FOA effect on variability of inter-joint
coordination. There was a general trend for FOA instructions to reduce variability of
coordination either in pre-contact or post-contact phase for both skilled and novice players (see
48
Figure 18). However, the reduced variability may mean differently for skilled and novice
players.
For skilled players, the variability of coordination for all interested inter-joint couplings
was significantly reduced from control by both or one of FOA instructions in the pre-contact
phase, suggesting that the imposed FOA instructions constrained players’ ability to make
adjustments on action component in search of optimal coordination pattern for setting. Even
though instructions are generally helpful for the performer, they should not be too restrictive to
prevent the performer from finding their own optimal movement (Pacheco et al., 2019). In the
post-contact phase, there was a significant drop of variability for inter-joint flexion-extension
couplings, and the FOA instructions had a small magnitude of effect to further reduce the
variability. This implied that there was a minimum need to adjust movements after the ball
contact and players maintained the adopted coordination pattern to complete the movement with
follow-through to ensure the consistency of ball trajectory. Such a movement solution was not
harmed by paying attention to either internal or external cues. The exception was that the
variability of coordination increased in the post-contact phase for shoulder-hip girdle rotation
coupling, particularly with external FOA, which indicates that skilled players might have
encountered some difficulty in stabilizing the shoulder-hip rotation with external FOA in the
follow-through stage. In sum, the FOA instructions contaminated the functional variability of
coordination that has been demonstrated by skilled players in the pre-contact phase, which might
also account for their reduced setting accuracy with FOA instructions.
Compared to skilled players, novice players demonstrated an overall lower variability of
coordination in all interested inter-joint couplings, which makes sense because freezing the
degree of freedom is necessary for developing the fundamental inter-joint coordination pattern
49
for a motor skill (Guimarães et al., 2020). Therefore, the high variability of coordination should
not be deemed as functional, but rather detrimental to the performance. In both pre-contact and
post-contact phases, we noticed that the FOA instructions either maintained or significantly
reduced the variability of coordination from control, suggesting that both internal and external
FOAs were somewhat useful for novice players to develop the fundamental coordination pattern
for setting. The only exception was that the variability of coordination for shoulder-hip rotation
coupling significantly increased from control with external FOA in the pre-contact phase, which
might be due to the spatially separate external cues that demand constant trunk rotations for
attention. Nevertheless, the FOA instructions, particularly the internal FOA, helped novice
players to reduce the variability of inter-joint coordination, which was required for developing
the fundamental inter-joint coordination patterns for successful setting. This finding is consistent
with a recent study (Gottwald et al., 2020) showing that internal FOA promoted the use of
proprioceptive information to yield a reduced movement variability and enhanced task
performance. To be noted, there was a trend (although not significant) in the current study for
novice players to also improve their setting accuracy with FOA instructions (see Figure 12).
Thus, with more trials of practice provided with FOA instructions, novice players are more likely
to find the appropriate inter-joint coordination patterns to increase their setting accuracy.
50
CONCLUSION
In conclusion, the current study examined the effects of broken-down FOA instructions on
volleyball setting performance of skilled and novice players, and the results supported previous
literature on motor expertise showing that skilled players outperformed novice players with
superior movement outcomes due to their ability to maintain an intermediate coordination pattern
and functional variability of inter-joint coordination prior to the ball contact. Although broken-
down FOA instructions failed to impact the mean inter-joint coordination patterns of all players,
they were significant to affect individual players to allow for the development of idiosyncratic
coordination patterns. The effect of internal and external FOA was found not to be different, which
might be due to the overloaded processing of broken-down attentional cues developed using the
same skill cues. Finally, both internal and external FOA instructions reduced the variability of
inter-joint coordination for all players, however, it was detrimental for skilled players as it
contaminated the functional variability required prior to ball contact leading to a decreased setting
accuracy, while it was beneficial for novice players as it facilitated the development of
fundamental coordination pattern for setting (even if it did not immediately yield the improved
setting accuracy).
LIMITATIONS OF THE STUDY
This study had several limitations: (1) the number of trials was relatively small, and it
may take more trials for the differential FOA effects to show on both skilled and novice players
given the complexity of the task; (2) Even the standard FOA instructions were provided and
compliance to the FOA instructions was assessed, different players may have different
interpretations to the instructions, thus, their application for setting may vary; (3) The
51
performance of skilled players may not be representative enough since they were a mixture of
Division 1 and club sports players; (4) the sample size within each skill level may not be large
enough to allow for detection of the congruent pattern of performance.
Future studies should explore the effect of FOAs on motor coordination with a reduced
number of attentional cues and consideration of individual preference. Perhaps, the true
effectiveness of FOA would be revealed by allowing the performer to choose one or two cues
from a list of broken-down attentional cues in either internal or external modality. In addition,
further research is warranted to examine the possibility of switching between using internal and
external FOA for motor learning and motor control.
PRACTICAL IMPLICATIONS
The findings of this study may suggest practical teaching or coaching of complex and
open sport skills. First, the practitioners should be cautious about using broken-down attentional
cues. Although the skill can be broken down into different components for part practice with
different attentional cues, these attentional cues shall never be used together when the skill is
performed as a whole, because simultaneously paying attention to multiple cues with
consciousness will result in the overloaded cognitive processing, leading to the degraded
performance. However, using attentional cues separately to correct errors or refine the skill
should be recommended. Second, the practitioners should be aware of the individual preference
in utilizing attentional cues. Some performers may respond to the internal FOA more than
external FOA or vice versa, and the FOA may impact motor coordination in different phases of
movement. Third, the skill level of the performer should be considered when giving FOA
instructions. While the conscious FOA instructions may be beneficial for novice performers to
52
find fundamental coordination patterns for the skill, they might be detrimental for skilled
performers as they interfered with well-developed motor automaticity and contaminated the
functional variability of motor coordination which is required for flexible and adaptive behavior.
53
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