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Graduate Theses and Dissertations Graduate School

6-30-2016

Using Expert Modeling and Video Feedback toImprove Starting Block Execution with Track andField SprintersApril DyalUniversity of South Florida, adyal@mail.usf.edu

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Scholar Commons CitationDyal, April, "Using Expert Modeling and Video Feedback to Improve Starting Block Execution with Track and Field Sprinters"(2016). Graduate Theses and Dissertations.http://scholarcommons.usf.edu/etd/6229

Using Expert Modeling and Video Feedback to Improve Starting Block Execution with Track

and Field Sprinters

by

April Dyal

A thesis submitted in partial fulfillment of the requirements for the degree of

Master of Arts in Applied Behavior Analysis Department of Child and Family Studies

College of Behavioral and Community Sciences University of South Florida

Major Professor: Raymond Miltenberger, Ph.D.

Kimberly Crosland, Ph.D. Sarah Bloom Ph.D.

Date of Approval: June 23, 2016

Keywords: Expert modeling, sports performance, track and field, video feedback

Copyright © 2016, April Dyal

ii

Table of Contents

List of Tables ................................................................................................................................ iii List of Figures ............................................................................................................................... iv Abstract ........................................................................................................................................... v Chapter 1: Introduction ................................................................................................................... 1 Chapter 2: Methods ......................................................................................................................... 5 Participants & Setting ......................................................................................................... 5 Materials ............................................................................................................................. 5 Target Behaviors and Data Collection ................................................................................ 6 Interobserver Agreement ........................................................................................ 7 Social Validity ........................................................................................................ 8 Treatment Integrity ................................................................................................. 8 Experimental Design ........................................................................................................... 9 Procedures ........................................................................................................................... 9

Baseline ................................................................................................................... 9 Video modeling and video feedback ..................................................................... 10

Follow up ............................................................................................................. 11 Chapter 3: Results ......................................................................................................................... 12 Social validity ................................................................................................................... 13 Chapter 4: Discussion ................................................................................................................... 16 References ..................................................................................................................................... 21 Appendices .................................................................................................................................... 28 Appendix A: Task Analysis for Starting Block Formation .............................................. 28 Appendix B: Social Validity Questionnaire-Coach .......................................................... 30 Appendix C: Social Validity-Athlete ................................................................................ 31 Appendix D: Treatment Integrity Form ............................................................................ 32

iii

Appendix E: USF IRB Letter of Approval ....................................................................... 33

iv

List of Tables

Table 1: Participants Social Validity Questionnaire Results .............................................. 15 Table 2: Head Coach Social Validity Questionnaire Results ............................................. 15

v

List of Figures

Figure 1: Graph for Participants ........................................................................................... 14

vi

Abstract

Correct formation during starting block execution is important for injury prevention and

obtaining maximum velocity during the sprint. Researchers in applied behavior analysis have

evaluated several procedures to improve performance in sports such as gymnastics, football, and,

golf. A promising method to improve sports performance is expert modeling plus video

feedback. However, there is little research on this method and it has yet to be evaluated with

sprinters in track and field. Therefore, the purpose of this study was to evaluate the effectiveness

of expert modeling and video feedback to improve form during block starts with track and field

sprinters. Results revealed marked improvement from baseline to intervention across all four

participants that was maintained at follow-up.

1

Chapter 1:

Introduction

In track and field, sprint starts are carried out in a number of ways including the standing

start, crouched start, or block start. According to Haugen, Tonnessen, and Seiler (2012), the

block start is one of the most effective ways to gain maximum velocity as quickly as possible

during sprint starts. The block start is one of the most difficult forms for a sprinter to execute

because it requires a series of complex movements, as the body of the sprinter must be at specific

angles to most effectively utilize the starting block apparatus and obtain utmost momentum.

A block start involves an apparatus referred to as a starting block. It has two wedges,

called pedals attached to a rod. The pedals serve as secured objects for the sprinter to push off,

creating a means for quick acceleration. Starting block formation involves a number of complex

motions in which the body is positioned in specific angles and the start is executed in one fluid

motion. The block start can be broken down into three distinct phases: bunched phase, drive

phase, and acceleration phase. During the bunched phase the sprinter is down on his or her hands

and knees with feet pressed against block pedals. This phase is critical because the hands, feet,

and legs must be in the suggested position to allow for optimal push off from the starting blocks.

Once in the drive phase, the sprinter uses the force applied to the blocks and is positioned in a

horizontal body stance. In this phase, the sprinters’ body is in the recommended angles to obtain

maximum velocity and to prevent injury. Acceleration, the final phase of the block start, begins

after the first two steps out of the blocks and ends 10 to 12 steps into the race. At the end of this

2

phase the sprinter is running in an upward position with knees high (Amneus et al., 2012;

Cowburn, 2005; Lee, 2007, 2014; Thomas, n.d.).

Behavioral procedures have been effective in improving skill execution in sports such as

football (Luiselli, Woods, & Reed, 2011; Reed, Critchfield, & Martens, 2006; Smith & Ward,

2006; Stokes & Luiselli, 2010), dance (Fitterling & Ayllon, 1983; Quinn, Miltenberger, & Fogel,

2015), gymnastics (Baudry, Leroy, & Chollet, 2006; Boyer, Miltenberger, Batsche, & Fogel,

2009), baseball (Osborne, Rudrud, & Zezoney, 1990); basketball (Kladopoulos & McComas,

2001; Romanowich, Bourret, & Vollmer, 2007), swimming (Dowrick & Dove, 1980; Hazen,

Johnstone, Martin, & Srikameswaran, 1990; Hume & Grossman, 1992), figure skating (Ming &

Martin, 1996), ice hockey (Rogerson & Hrycaiko, 2002), golf (Guadagnoli, Holcomb, & Davis,

2002), track and field (Maryam, Yaghob, Darush, & Mojtaba, 2009; Shapiro & Shapiro, 1985),

and tennis (Allison & Ayllon, 1980). A number of methods such as instruction, modeling, public

posting (Brobst & Ward, 2002; Ward & Carnes, 2002), goal setting (Ward & Carnes, 2002)

motion detection systems (Angelescu & Reske, 2006) and various forms of feedback (Boyer et

al., 2009; Quinn et al., 2015) have been used in the field of applied behavior analysis to enhance

athletic performance.

Performance film is widely used in athletics as a method of feedback to improve player’s

performance. It involves video recording an athlete performing a skill and playing it back while

providing positive and corrective verbal feedback on the performance. This method of feedback

has only been demonstrated as effective in a handful of sports such as martial arts (Benitez

Santiago & Miltenberger, 2016), yoga (Downs, Miltenberger, Biedronski, & Witherspoon,

3

2015), horseback riding (Kelley & Miltenberger, 2016), and tennis (Van Wieringen, Emmen,

Bootsma, Hoogesteger, & Whiting, 1989).

Hazen et al. (1990) compared a standard coaching method with video feedback to

improve swimmers’ performance of two swimming strokes, the freestyle and the backstroke

racing turn. Each swimming stroke was assessed using a task analysis breaking down the

components in each skill and marking each component as correctly or incorrectly performed.

Employing a multiple baseline across participants, the results demonstrated that video feedback

was more effective than standard coaching across all participants. Furthermore, in the follow-up

phase, two out of the three participants maintained the skill improvement.

Guadagnoli et al. (2002) evaluated golf swing performance with 30 golfers who were

randomly assigned to one of three groups: a video, verbal, or self-guided instruction. Each

participant hit 15 golf balls with a 7-iron club consecutively in all phases. Results revealed that

the verbal and video feedback groups showed improvement in the targeted skill during follow-up

but the self-guided group did not. Furthermore, data indicated that the video-feedback group

showed the most improvement in skill performance.

In some studies expert modeling has been added to video feedback to improve complex

athletic performance (e.g. Boyer et al., 2009; Rikli & Smith, 1980). Expert modeling involves

video recording of an elite performer executing a specific skill and showing the performance to

the athlete to prompt correct execution of the skill. When combined, video modeling can show

the athlete the expected performance and video feedback can provide reinforcement when with

athlete achieves or approximates the behavior shown in the video or provide correction so the

athlete can more closely match the modeled performance.

4

Rikli and Smith (1980) used expert modeling with video feedback to improve tennis

serving form. The study compared three feedback groups with a control. The feedback groups

received expert modeling and video feedback either the first day of instruction (early group), on

the third day of instruction (mid-instruction group), or both the first day and third day

(combination group). The control group did not receive feedback on their performance. During

each video feedback session, the participant performed the skill followed by an opportunity to

compare his or her performance with a video recording of an expert model executing the skill

side-by-side. Results revealed the three feedback groups showed a significant improvement in

serving form as compared to the control but did not differ from each other. These findings

indicate that expert modeling and video feedback is an effective treatment package for improving

performance of tennis serving form.

Boyer et al. (2009) also used expert modeling with video feedback to enhance the

performance of three gymnastic skills - the kip cast, giant, and clear hip circle. Results showed

improved skill performances across all participants in the three skills during video modeling and

feedback phases. Moreover, the skills maintained over time for all of the participants. Overall,

the results indicated that expert modeling and video feedback were more effective than typical

practice and coaching alone for teaching a complex skill.

Because expert modeling and video feedback have been shown to be effective in

improving skill acquisition in sport performance in only two studies and because the procedure

has yet to be evaluated with starting block formation of track and field sprinters, more research is

needed. Therefore, the purpose of this study is to examine the use of expert modeling plus video

feedback to improve starting block formation with track and field sprinters.

5

Chapter 2:

Methods

Participants and Setting

Four sprinters, age 12 to13-years-old, participated in the study. Alex, a 13-year old girl,

had been running track for 3 years. She ran the 200-meters and the 400-meters. Lindsey, a 12-

year old girl, had been running for 5 years. She ran in the hurdles, 200-meters, and long jump.

Lauren, a 13-year old girl, had been running for 2 years. She ran the 200-meters, 200-meter

hurdles, 400-meters, and long jump. Alison, a 13-year old girl, had been running for 2 years. She

ran in the 100-meters, 200-meters, 400-metters, and high jump. The study was conducted on a

track where the participants usually practice track and field during regularly scheduled practice

times 3 days a week for 2 hours each practice. All participants were recruited from a local track

and field traveling team that participates at local, regional, state and national level meets. A flyer

was given to all sprinters on the team for recruiting purposes. A criterion to participate included

experience running in the 100-meters and/or the 200-meters sprints either during practices and/or

during competitions as well as experience with block starts. Each participant was evaluated on

the percentage of steps correct using a task analysis and was required to score 80% or less to

participant in the study. Any participant that did not meet recruiting requirements was not

included in the study.

6

Materials

The materials used for this study include an iPad® second generation for video recording

with software to present participants’ performance. The Dartfish® application downloaded from

the Apple® app store provided the means to display side-by-side video with an expert model

video, viewings of all recorded videos in slow motion, and visually display angels in degrees.

Two expert modeling videos were selected from YouTube® video database, one of a female

USA gold medalist sprinter, Sanya Richards-Ross, and the second of a male Jamaican gold

medalist sprinter, Asafa Powell. The female expert model was chosen to serve as the expert

model due to the rapport built with the participants when they met her previously and the male

model was chosen to ensure all necessary angles in the three phases could be clearly viewed.

One video displayed a slow motion view and the other in regular speed. The BrainMac® Sports

Coach starting block calculator was used to determine participant’s block setting (Mackenzie,

2001). BrainMac® block calculator uses the angles of the legs in the starting block position (i.e.,

120 and 90 degrees) along with specific measurements of the runner and mathematical

calculations to individualize pedal block settings. A Canon® VIXIA HF M500 video camera and

tripod was used to record each participant’s session for treatment integrity. Lastly, an 18-step

task analysis was created by reviewing literature on the block start positions (Cowburn, 2005;

Lee, 2007, 2014; Rosenbaum, n.d.; Thomas, n.d.) and breaking the skill down into observable

and measureable steps. University of South Florida men’s head sprinting coach with more than 5

years of coaching at a college-elite level and 727 Track Club head coach with more than 10 years

of coaching experience at the elite level viewed the task analysis and validated each step.

7

Targets Behaviors and Data Collection

The dependent variable was number of correct steps completed during starting block

execution (see appendix A). For example, in the set position hips should rise slightly to the

position above shoulders, head and neck in line with the spine, shoulders vertical or slightly

forward of hands, front leg knee at a 90 to 99 degree angle, rear leg knee at a 120 to 130 degree

angle, and feet firmly pressed against the block pedal. Data were collected via video recording

using the 18-item task analysis and reported as the percentage of correct steps completed. This

was done by reviewing each attempt in slow motion and marking yes or no on the task analysis.

“Yes” was marked if the participant performed the step correctly and “no” was marked if the

participant performed the step incorrectly. This process was performed for each participant after

each session was completed during baseline and intervention phases.

Interobserver Agreement

A second observer recorded the steps completed correctly during starting block execution

on a minimum of 43% of sessions to assess interobserver agreement (IOA). Agreement was

calculated by dividing the number of steps of agreement between the two observers by the total

number of steps. Each research assistant was trained to collect data using one or both of the

expert video models used in the study and the written task analysis. I walked the research

assistant through an example of each step in the task analysis providing a visual example, using

an expert model video and novel runner, and verbally assisted on what each step should look like

to score the step as “yes” or “no” on the data sheet. First in screenshot form, allowing the

assistant to view a correct response and an incorrect response of each step, followed by a

demonstration of the functions in the Dartfish® application. Next, the research assistant

8

practiced scoring each step in the task analysis while viewing various block execution videos in

slow motion. Once scoring was completed I reviewed it and provided corrective feedback and

specific praise. Each research assistant scored the task analysis at 100% correct at the end of

training. If scoring fell below 80% during the study, a booster training would be provided, but it

was not needed.

For Alex, IOA data collected for 45% of sessions averaged 94% agreement (range: 88%-

96%). For Lindsey, IOA data collected for 43% of sessions averaged 94% agreement (range:

90%-98%). IOA data collected for Lauren in 43% of sessions averaged 91% agreement (range:

81%-100) and for Alison IOA data collected in 43% of sessions averaged 93% agreement (range:

83%-100%).

Social Validity

Social validity of the intervention was measured using a questionnaire with ratings on a

5-point Likert-type scale. Two different questionnaires were administered, one to the head coach

(see appendix B) and another to the participants (see appendix C) following completion of the

final phase. The questionnaires assessed the acceptability of the intervention procedures, ease of

implementation, how helpful they thought it was, and if they would recommend it to others.

Treatment Integrity

Treatment integrity (TI) data were collected by a research assistant on an average of 51%

(range: 18%-71%) of all sessions across participants to ensure procedures were carried out as

stated (see appendix D). Total number of steps varied depending on whether a participant was in

baseline or intervention phase at that time. The treatment integrity form included six steps in

baseline and follow-up and 24 steps in intervention. The research assistant was trained on the

9

experimental procedures for baseline and intervention prior to examination. Training was held in

person using a video recording of a novel subject as the runner, and the treatment integrity

checklist. Training involved reviewing each correct procedure used in baseline and intervention.

Exact agreement was calculated by dividing the number of agreements by the number of steps in

the task analysis then multiplying that total by 100 to get a percentage of agreement. Data

revealed 99.75% agreement across all participants. The mean TI data were 100% for Alex, 100%

for Lindsey, 96.5% for Lauren (range: 93%-100%), and 100% for Alison.

Experimental Design

A multiple baseline across participant’s design was employed, with baseline intervention,

and follow-up phases showing the percentage of correct steps completed in each assessment for

each participant. Intervention phases were staggered across participants.

Procedures

I met with the head coaches before data collection commenced to view and validate the

expert model video, review the items on the task analysis, review procedures used during all

phases, discuss potential participants, and provide a brief overview of procedures. I then met

with all potential participants to conduct an assessment of their qualification for the study. I

explained the recording procedure and allowed for time to discuss any concerns and/or answer

any questions. I asked those whom met the requirements and were interested in participating to

review and sign an assent form and asked for their legal guardians to review and sign a consent

form. Copies of each of the forms were provided for each participant’s legal guardians. Once all

consent forms were signed and returned data collection commenced.

10

Baseline. Sessions were held on the practice track at the team’s usual practice time.

Typical practices involves instructions, practice, and occasional feedback implemented in a

somewhat unsystematic fashion. The head coach of the team informed me of the predetermined

settings of the block pedals for each participant and communicated any changes in settings

before each training session began. When arriving at the track, equipment was set up to simulate

a typical practice session of block start practice. In other words, the participant retrieved starting

blocks and placed them in a lane on the track then positioned block pedals. Participants were

required to stretch with the team or individually before sessions commenced. All recording

equipment was prepared in advance for recordings. A verbal cue was given to signal the

participant to get into the starting blocks. Three trials were conducted consisting of the

participant getting into starting blocks and sprinting for 20 to 30 m. No feedback was provided to

the participant in baseline.

Video modeling and video feedback. The video modeling by experts with video

feedback condition involved showing the participant a video of an expert modeling the skill in

regular speed and again in slow motion. Video feedback included video recording a block start,

displaying the video, and providing verbal feedback. To begin, the participant was asked to

perform the skill while being recorded on the Dartfish® software application. Immediately

following the block start, the participant was provided with video feedback of her performance

on the iPad first in regular speed and then again in slow motion. During the feedback, I provided

descriptive praise for steps completed correctly using statements such as, “You did a nice job

keeping your head down” or “I really liked the way you remembered to keep your back foot

pressed firmly on the block pedal.” Corrective feedback describing behaviors to be improved

11

was provided using statements such as, “let’s remember to keep your back foot pressure firmly

against the pedal until take off” or “remember to keep your head down while sitting in the

blocks.” The participant’s performance video was then displayed in split screen mode with the

participant’s video on the left side or top of screen and expert model video displayed on the right

or bottom, both in slow motion. Following the side-by-side viewing the participant was asked to

perform the skill again while being recorded. These procedures were carried out until three

attempts were completed with video modeling and video feedback. Video recordings of each

assessment attempt began by zooming in on the displayed numbers on the starting block spine to

ensure participant correctly placed block pedals. Once the training session was completed the

participant was asked to execute the start three times without feedback to assess training. During

the first attempt at assessment participants were required to reset the blocks into the same lane

used in training and to place the block pedals in predetermined slots. The block pedals were not

moved between assessments.

Follow up. Follow up data were collected 2 weeks after the conclusion of intervention.

Procedures for follow up were conducted as in baseline, assessing three block start attempts with

no feedback provided.

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Chapter 3:

Results

All participants demonstrated an increase in correct block start form after the introduction of an

expert model and video feedback (see figure 1). Baseline levels were variable for all participants.

At the onset of expert modeling and video feedback all participants’ scores rose well above their

scores in baseline. Each participant demonstrated slightly variable data throughout intervention

but no participant ever dropped below baseline levels. Baseline and intervention means were

50% (range 33%-72%) and 88% (range 77%-94%) for Alex, 56.5% (range 38%-66%) and 92.5%

(range 83%-100%) for Lindsey, 46% (range 22%-61%) and 92.5% (range 83%-100%) for

Lauren, and 63% (range 38%-77%) and 91.5% (range 83%-100%) for Alison. Three participants

Lindsey, Lauren, and Alison achieved 100% a number of times during the intervention phase.

After a 2-week period, follow-up data revealed maintenance of the gains with a mean of 96%

(range 94%-100%) for Alex, 90% (range 88%-94%) for Lindsey, 92% (range 88%-94%) for

Lauren, and 94% (range 88%-100%) for Alison.

Arrows in baseline and intervention phases indicate when the participants received block

start training (practice and feedback) during their regular track practice (see Figure 1). Alex

received such training in one practice session only during intervention. Lauren received block

start training in one practice session of baseline and Alison received it in two sessions of

13

baseline. Lindsey received block start training in one practice session during baseline and one

during intervention. Based on the timing of such training and visual inspection of the data, it

appears that block start training during regular practice sessions did not influence the data. On

the other hand, the intervention produced an immediate increase in the percentage correct.

Social validity. Social validity results demonstrate an overall strong liking of the

program across all four participant and head coach. Table 1 illustrates the results for each

question asked to each participant. Table 2 illustrates the results for each question asked to the

head coach. When participants were asked what they liked and did not like about the program

their general response was that they enjoyed how the program breaks down all the steps in the

block start making the skill easier to learn than ever. Responses also indicated an overall

delectation with the feedback provided and the style in which it was delivered. No participant

indicated a disliking to the program. The head coach’s overall feedback on the program was a

strong liking as well. When asked what he liked and did not like about the program he noted that

it gave a more intimate one on one training with the runners allowing them more time to grasp

the technical skill and benefit them in the future.

14

Figure 1. The percentage of correct steps completed during baseline, intervention, and follow-up for four participants.

15

Table 1

Social Validity Results-participants

Alex Lindsey Lauren Alison

1. I enjoyed participating in the training

program 5 5 5 5

2. I think the training program was helpful 5 5 5 4

3. The training program did not take too

much time from regular practice 5 5 4 4

4. I would recommend this program to

others 4 5 5 4

Note: Likert scale of 1 to 5. A score of 1 represents strongly disagree and 5 represents strongly

agree.

Table 2

Social Validity Results-head coach

1. The procedures were helpful for improving block start 4

2. I would recommend this procedure to others 5

3. The procedures were easy to use 5

4. The program did not disrupt normal practice 5

Note: Likert scale of 1 to 5. A score of 1 represents strongly disagree and 5 represents strongly

agree.

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Chapter 4:

Discussion

Adding to the literature on effective feedback methods in sports performance (Benitez

Santiago & Miltenberger, 2016; Boyer et al., 2009; Downs et al., 2015; Kelley & Miltenberger,

2016; Van Wieringen et al., 1989) this study showed that expert modeling and video feedback

improved athletic skill performance. All four participants substantially improved on block start

form during intervention compared to baseline levels.

The results of this study exceeded those found in Boyer et al. (2009) that examined the

use of expert modeling and video feedback to improve the performance of three gymnastic skills.

Like Boyer et al. this study examined a packaged feedback method with a youth population on a

complex sport performance skill, however this study found higher levels of performance during

intervention and follow up. This study expands on the research that shows that providing an

athlete with an expert model and video feedback immediately following a trial performance will

increase correct execution of that skill (e.g., Boyer et al., 2009; Rikli & Smith, 1980).

It should be noted that half way through the study all but one participant, Alex, started

wearing their running spikes instead of tennis shoes during each session. Exact data points for

each participant’s first time wearing the spikes during the study are as followed; Lindsey on the

16th data point, Lauren the 22nd, and Alison the 10th. A change in shoe wear is noted because it

may have had an effect on the participants’ ability to perform specific steps, such as “majority of

front foot pressed firmly against pedal” in the bunched position correctly at consistent rates.

17

Inspection of the data in Figure 1 does not indicate any change in the data at the point that the

participants started wearing spikes.

Adding the expert model to the video feedback seemed to add value and was worth the

extra time it took to combine it with video feedback. Without having the expert model it would

have made providing detailed feedback on particular steps in the task analysis more difficult. For

example, as the video model showed how the runner’s shoulders should be leaning forward

during the set position and how the front foot should be pressed firmly against the block peddle

in the bunch position to the runners.

Although this study revealed marked improvements of participant performance, it did not

come without limitations. The 18-step task analysis used in this study only covered the basic

steps and angles required to correctly preform a block start. A block start should be performed in

one fluid motion requiring the sprinter to have agile flexibility and strength (Cowburn, 2005;

Lee, 2007, 2014; Rosenbaum, n.d.; Thomas, n.d.). A range was set for the angle positions instead

of one specific angle during the set and drive phase. This range was set when considering the

immaturity of the participants’ physical strength. Setting a range gave the sprinter an increased

opportunity of contacting the reinforcing property of performing that step correctly. Although the

task analysis used during this study may not be sensitive enough to measure improvement in an

elite sprinter’s block starts, it is sufficient for use with amateur runners.

While scoring the participants assessment videos it was discovered that steps such as

“hands positioned evenly apart at shoulder-width or slightly wider than shoulder-wide” and

“head and neck are in line with spine measuring from the top of the head to the lower back” were

difficult to clearly see through viewing the recordings. This was due to only having one camera

18

displaying one side of the runner during the filming of the performance. This lack of multiple

camera angles could have hindered the scoring results of a second observer not present during

assessments.

Unforeseen extraneous variables such as inconsistent attendance, frequent insect

swarming, and a distractible environment made it difficult to collect data throughout the study.

On one occasion insect swarms prevented data collection. The bug filled environment was

resolved with the use of bug spray in subsequent sessions while the attendance issue and

distractible environment was difficult to control. Due to attendance inconsistencies and time

sensitivity of the study one participant started baseline but never advanced to intervention and

thus was dropped.

After about five to 10 sessions in intervention phase participants started telling me what

steps they thought they might have gotten wrong before any feedback was provided and the

majority of the time the participant was right. This is a potentially important finding because it

suggests that the athletes acquired the ability to assess their own performance in real time even

before viewing the video. This increased awareness of performance in real time could be one

mechanism that accounts for the effectiveness of the intervention.

In addition to the clear increase in performance shown in the data, after the first track and

field meet participant’s parents and the team coaches reported that they saw improvement in the

participants’ block starts during the meets. These anecdotal reports, coupled with the social

validity data, suggest that the changes were socially significant.

In summary this study is the first to evaluate an expert model and video feedback to

improve block start formation with a young population. The results showed clear effects from

19

baseline to intervention phases confirming that the intervention increased the percentage of

correct steps executed consistently during a block start, more so than the unsystematic training

used by typical track and field coaches.

Future research could develop a measurement system that is more sensitive to the elite

sprinter. In considering creating a more sensitive measurement system, it would be valuable to

add a step to the “set position” to measure whether the runner is looking down the lane at the

finish line. This additional step could have positive effects on sprinter’s body angles during the

first couple of steps out of the blocks potentially aiding in the execution of advised angle position

consistently. Research should consider providing multiple camera angles to provide a more

accurate assessment of steps used to evaluate the athlete’s performance and a better view for the

participant to see during video feedback. Future replication should consider evaluating block

start performance in a dyad format. For example, training one athlete on the correct steps and

having that person teach another team member. Using a dyad assessment and intervention could

cut down on the amount of time spent providing feedback on block starts with each sprinter. In

addition, the friendly competition on who could improve the most and the fastest might function

as an establishing operation for improved performance. Adding peer mentoring and/or pyramidal

training with an advanced sprinter and having that person work one on one with other younger or

less experienced runners would also cut down on the amount of time the coaches have to spend

providing feedback. Future research could also consider conducting assessment probes during

track meets to evaluate whether the sprinter would maintain correct block start formation in

completive environments along with having secondary effects of improving race times. Finally

20

research should evaluate whether the improved performance resulted in improved times during

the sprint.

21

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Appendices

Appendix A: Task Analysis for Sprint Block Formation Sprint Block Formations

YES NOBunched into blocks

Blocks are positioned in the centered lane

Block pedals are correct distance from the starting line (approximately 1 to 1.5 ft. from starting line)

Foot block at correct angles (define individually)

Feet correctly located in blocks (majority of the foot in front pedal is pressed back against block pedal) and vertically positioned on the pedal (i.e. heal does not fall to the side)

Fingers behind the line form a high bridge (thumb and forefingers are the only part of hands touching track with palm of hands off the ground) and are just behind or touching the starting (i.e. the white line)

Hands positioned evenly apart at shoulder-width or slightly wider than shoulder-width

Shoulders are back and in line or slightly forward of the hands

Arms are straight but the elbows are not in a locked position

Head and neck in line with spine (i.e. head is not leaning to one side or another) neck should appear to be in a relaxed position

Set Position

Raise hips slowly to a position above the shoulders

Head and neck are in line with the spine measuring from top of head to lower back

Shoulders are vertical or slightly forward of hands

Front leg: knee (power leg) measuring from hips to heel; center of angle at the middle-back of knee at a 90-99 degree angle

Rear leg: knee (lead leg) measuring from hips to heel; center of angle at the middle-back of knee at a 110-130 degree angle

Feet (both front & rear foot) are pressed against the block pedal

Drive phase (First step out of the blocks)

29

In a wide range of motion forcefully drive arms in opposite directions (one moving forwards and the other moving backwards).

The arm that is on the same side as the leg closest to the starting line moves forward first.

From the top of head down to toes of back foot measure 45-90 degree angle

30

Appendix B: Social Validity Questionnaire- Coach The procedures were helpful for improving the block starts Strongly disagree

1 Disagree

2 Neutral

3 Agree

4 Strongly agree

5 I would recommend this procedure to others Strongly disagree

1 Disagree

2 Neutral

3 Agree

4 Strongly agree

5

The procedures were easy to use Strongly disagree

1 Disagree

2 Neutral

3 Agree

4 Strongly agree

5 The procedures did not disrupt normal practice Strongly disagree

1 Disagree

2 Neutral

3 Agree

4 Strongly agree

5 What did you like and not like about the procedure?

31

Appendix C: Social Validity Questionnaire- Athlete I enjoyed participating in the training program Strongly disagree

1 Disagree

2 Neutral

3 Agree

4 Strongly agree

5 I think the training program was helpful Strongly disagree

1 Disagree

2 Neutral

3 Agree

4 Strongly agree

5 The training program did not take too much time from regular practice Strongly disagree

1 Disagree

2 Neutral

3 Agree

4 Strongly agree

5

I would recommend this program to others Strongly disagree

1 Disagree

2 Neutral

3 Agree

4 Strongly agree

5 What did you like and not like about the program?

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Appendix D: Treatment Integrity Form Baseline YES NO

Three trials were ran with each participant

No feedback was provided throughout session

Video modeling and video feedback Training Trials

Had the participant view expert model video regular speed

Had the participant view expert model video in slow motion

The participant was asked to preform a block start

Recording was made of participant’s performance using the Ipad®

The participant was shown the video of performance on Dartfish® application in regular speed

The participant was shown the video of performance on Dartfish® application in slow motion

The participant was provided with descriptive praise on last performance

The participant was provided with corrective feedback on performance (if needed)

The participant was shown her performance video side-by-side the expert model video in slow motion using the Dartfish® application

During the side-by-side viewing the participant received feedback on performance

Training assessments

The participant was asked to preform block start three times consecutively

The participant did not receive feedback on performances

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Appendix E: USF IRB Approval Letter

34