University of Southern California Dissertations and Theses

Behavioral coaching for athlete health behaviors

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Behavioral coaching for athlete health behaviors

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BEHAVIORAL COACHING FOR ATHLETE HEALTH BEHAVIORS

by

Isabella Maria Camello Tan

A Thesis Presented to the
FACULTY OF THE USC DAVID AND DANA DORNSIFE COLLEGE OF LETTERS, ARTS
AND SCIENCES
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
MASTER OF SCIENCE
APPLIED BEHAVIOR ANALYSIS

May 2020

Copyright 2020 Isabella Maria Camello Tan
ii

TABLE OF CONTENTS
List of Figures………………………………………………………………………………….…iii
Abstract……………………………………………………………...…………………………....iv
Chapter 1: Introduction…………………………………………………………….…………...…1
1.1 Behavior Analysis and Sports……………………………………………....………….1
1.2 Performance Diagnostic Checklist…………………………….……....………………4
1.3 The Current Study…………………………………………………….……..…….…..5
Chapter 2: Method………………………………………...….…………………….……………...6
2.1 Participants and Setting………………………………………………….…………….6
2.2 Materials and Measures………………………………………………….…………….7
2.3 Procedures…………………………………………………………....………………..7
Chapter 3: Results……………………………………………………………………….……….10
Chapter 4: Discussion……………………………………………………………………..……...12
References………………………………………………………………….…………………….16
Appendices……………………………………………………………………………………….25
Appendix A: Pittsburgh Sleep Quality Index……………………………………………..25
Appendix B: Performance Diagnostic Checklist…………………………………………27
Appendix C: Social Validity……………………………………………………………...29

iii

LIST OF FIGURES
Figure 1: Performance Diagnostic Checklist Results……………………………………………30
Figure 2: Intervention Results……………………………………………………………………31

iv

Abstract
Applied behavior analysis methods have often been used in the field of sports. Intervention
packages have been created to facilitate acquisition of new skills, improve technique for existing
skills, and promote better practice and competition behaviors. Though the efficacy of ABA
intervention techniques has been demonstrated multiple times, there is a paucity of research
regarding assessment in sports. The Performance Diagnostic Checklist (PDC) is an assessment
tool often used in organizational settings to identify barriers to efficient performance. This study
evaluated the utility of the PDC for improving health-related behaviors among athletes. Using a
multiple baseline design, interventions based on the PDC were evaluated with two students and
one alumnus at a university. Results were mixed but overall, there was an increase in the target
behavior chosen by the participants upon implementation of the intervention.
1

Behavioral Coaching for Athlete Health Behaviors
Chapter 1: Introduction
1.1 Applied Behavior Analysis and Sports
Applied behavior analysis techniques have been used to address a wide variety of athletic
behaviors. The efficacy of ABA strategies has been demonstrated with different sports and
physical activities including dance (e.g., Vintere & Poulson, 2010), yoga (e.g., Downs,
Miltenberger, Biedronski, & Witherspoon, 2015), swimming (e.g., Schonwetter, Miltenberger, &
Oliver, 2014), martial arts (e.g., Harding, Wacker, Berg, Rick, & Lee, 2004), football (e.g.,
Harrison & Pyles, 2013), soccer (e.g., Holt, Kinchin, & Clarke, 2012), tennis (e.g., Buzas &
Ayllon, 1981), gymnastics (e.g., Boyer, Miltenberger, Batsche, & Fogel, 2009), running (e.g.,
Wack, Crosland, & Miltenberger, 2014), golf (e.g., Fogel, Weil, & Burris, 2010), basketball
(e.g., Kladopoulos & McComas, 2001), pole jumping (e.g., Scott, Scott, & Goldwater, 1997),
horseback-riding (e.g., Kelley & Miltenberger, 2016), skating (e.g., Anderson & Kirkpatrick,
2002), lacrosse (e.g., DePaolo, Gravina, & Harvey, 2018), rugby (e.g., Mellalieu, Hanton, &
O’Brien; 2006), and baseball (e.g., Heward, 1978).
Behaviors and populations targeted. While most of these studies have focused on
acquisition or refinement of athletic skills, other related behaviors have also been targeted. For
instance, one study focused on reducing emotional outbursts (Allen, 1998), while some have
focused on practice behaviors (e.g., Hume & Crossman, 1992). Participants in the studies have
ranged from complete novices (e.g., Ziegler, 1987) and child athletes (e.g., Tai & Miltenberger,
2017) to high school/collegiate players (e.g., Stokes, Luiselli, & Reed, 2010) and international
level competitors (e.g., Scott et. al, 1997). Techniques have also been used with teams or groups
2

(e.g., Komaki & Barnett, 1977), coaches and teachers (e.g., Quinn, Miltenberger, & Fogel,
2015), and individuals with disabilities (e.g., Lambert et al., 2016).
Techniques used. While some studies evaluated a specific technique (e.g., self-directed
stimulus cues, Ziegler, 1987; visual cues, Osborne, Rudrud, & Zezoney, 1990; attentional shift
training, Ziegler, 1994; video feedback, BenitezSantiago & Miltenberger, 2016), many of the
studies utilized multiple techniques in an intervention package. Common components included in
these packages include some form of feedback (e.g., Allison & Ayllon, 1980); goal setting, both
coach-determined (Brobst & Ward, 2002) and athlete-determined (e.g., Mellalieu et al., 2006);
variations of self-monitoring/self-management (e.g., Wolko, Hrycaiko, & Martin, 1993); task
analyses (e.g., Downs et al., 2015); differential reinforcement (e.g., Stokes et al., 2010); and
modeling (e.g., Boyer et al., 2009). Other techniques that have been studied include auditory
prompting (Scott et al., 1997), group contingencies (e.g., Hume & Crossman, 1992), and forms
of punishment, such as positive practice and timeout (Allison & Ayllon, 1980). Interventions for
individuals with disabilities have used methods such as DTT (Lambert et al., 2016), modeling,
and descriptive feedback (Bord, Sidener, Reeve, & Sidener, 2017).
Specific teaching methodologies have also been developed. One such methodology is
TAGTeach, which is based on clicker training. In TAGTeach, specific tag points (target
behaviors) are selected based on a task analysis. Engagement in these target behaviors will result
in some form of audio feedback (e.g., Fogel et al., 2010). Behavioral skills training (BST) has
also been adapted to fit athletic settings. BST has three components: 1) verbal instruction, 2)
modeling, and 3) role playing with feedback (e.g., Tai & Miltenberger, 2017).
Areas for further study. While this review does not evaluate all existing studies wherein
ABA techniques were applied to sports and fitness behaviors, the research presented here
3

demonstrates that programs using behavior analytic techniques have largely been successful in
improving specific aspects of athletic performance. Although the utility of many intervention
packages has been demonstrated across a variety of different populations and behaviors, certain
areas are still in need of study. In their review of the use of ABA for sports, Luiselli and Reed
(2015) state that little to no research has included any formal preference assessment prior to the
onset of intervention. Furthermore, they found that functional assessments are rarely conducted
in the field of sports.
Apart from the gaps that Luiselli and Reed (2015) identified, an area that has received
little to no attention within the field of ABA is athlete health-related behaviors. While research
that has focused on improving an athlete’s technique with the goal of reducing injury exists (e.g.,
Tai & Miltenberger, 2017), health-related behavior remains an under-researched area in ABA.
ABA techniques have been demonstrated to be effective for improving health behaviors
in general (interested readers can see Normand, Dallery, & Ong, 2015 for a review of research).
In addition to traditional ABA methods, Acceptance and Commitment Therapy (ACT) has also
been evaluated in relation to health. Some areas that have been studied include exercise (e.g.,
Ivanova, Jensen, Cassoff, Gu, & Knäuper, 2015; Ivanova, Yaakoba-Zohar, Jensen, Cassoff, &
Knäuper, 2016), disease management (e.g., Haji Seyed Javadi et al., 2019), substance abuse (e.g.,
Twohig, Shoenberger, & Hayes, 2007; Luoma, Kohlenberg, Hayes, Bunting, & Rye, 2008), and
sleep (e.g., Daly-Eichenhardt, Scott, Howard-Jones, Nicolaou, & McCracken, 2016) among
others. While many studies are preliminary in nature, there is a growing body of research to
support the efficacy of ACT for improving health-related behaviors. Overall, a substantial
amount of research has demonstrated the effectiveness of ABA in sports but very little on
4

increasing health-related behaviors in athletes and less still on the use of functional assessments
in ABA-based interventions for athletes.
1.2 The Performance Diagnostic Checklist (PDC)
The Performance Diagnostic Checklist (Austin, 2000) is an assessment tool that examines
variables that maintain poor performance in organizations. The PDC was developed using the
results of Austin’s (1996, 1998a, 1998b; as cited in Austin, 2000) studies about managerial
behavior. These studies found that managers who consistently produced the best solutions when
faced with problems asked questions that fell into one of four categories: a) antecedents, b)
equipment and processes, c) knowledge and skills, and d) consequences. The PDC is comprised
of 20 questions that address these 4 areas. The PDC has been modified to be appropriate for use
with employees in the human services industry (PDC- Human Services; Carr, Wilder,
Majdalanay, Mathisen, & Strain, 2013; Carr & Wilder, 2016), and to assess barriers to engaging
in safe work behavior (PDC-Safety; Martinez-Onstott, Wilder, & Sigurdsson, 2016).
Populations and settings. Interventions based on the PDC have been evaluated with
different participants such as employees in a coffee shop (Pampino, Heering, Wilder, Barton, &
Burson, 2004), landscapers at a university (Martinez-Onstott et al., 2016), individuals with
disabilities working at a thrift shop (Smith & Wilder, 2018) and employees in a restaurant
(Rodriguez et al., 2006). In all four studies, creating behavioral interventions that were based on
the areas identified as problematic on the PDC resulted in improved performance in the target
behaviors compared to baseline.
The necessity of the PDC. While the aforementioned studies showed clear
improvements following the implementation of the intervention, a question posed by some
authors is whether similar results could have been attained without the use of the PDC. This
5

question has been addressed by several studies which compared interventions indicated by the
PDC with arbitrarily selected interventions that were not indicated by the PDC. Studies have
been conducted with therapists (Wilder, Lipschultz, & Gehrman, 2018; Ditzian, Wilder, King, &
Tanz, 2015; Carr et al., 2013), and with paraprofessionals at a preschool (Bowe & Sellers, 2018).
In all four studies, interventions indicated by the PDC produced superior results compared to
interventions not indicated by the PDC.
PDC and sports. Much of the research with the PDC has been in the field of
Organizational Behavior Management (OBM). Research using the PDC for sports interventions
are rare. The one study, of which we are aware, that has done so was conducted by DePaolo and
colleagues (2018). They utilized the PDC to increase pass naming in a college lacrosse team. In
their study, antecedents and consequences were identified as problematic areas, and an
intervention package consisting of prompting (from the coach) and a negative reinforcement
group contingency (reducing the number of sprints at the end of training) was implemented.
Their intervention package was able to increase the frequency of pass naming among the team.
1.3 The Current Study
The purpose of this study is to create individualized, assessment-informed interventions
to improve overall self-care behaviors in athletes. The study had two main research questions: 1)
Can the PDC identify barriers to engagement in health behaviors? 2) Can addressing the barriers
identified by the PDC lead to improved performance in the domain of interest? This study
incorporated participant preference and social validity into the intervention by having each
participant identify their own specific goals and make decisions regarding the intervention
techniques used.

6

Chapter 2: Method
The study was conducted using a combination of in-person study visits, phone calls, text
message contacts, and video conferences. Study visits were conducted once a week, barring
holidays and unforeseen circumstances (e.g., participant requests for cancellation, researcher
illness).
2.1 Participants and Setting
The study was conducted on the campus of a large private research university in a major
metropolitan area. Participants were recruited through an online bulletin, flyers posted around
campus, and an electronic invitation sent to the athletic clubs in the university. Nine individuals
consented to participate in the study. Of the nine, three individuals completed the study. Two
individuals participated as pilot participants, two participants elected to terminate their
participation after they deemed their baseline performance to be adequate, one individual’s
participation was terminated due to illness, and one individual elected to terminate participation
for personal reasons.
Rey. Rey was a sophomore at the university. She was a triathlete and her primary
concern was to increase her nightly sleep duration.
Leia. Leia was a first-year doctoral student in engineering. She participated in kickboxing
and yoga. Leia aimed to improve her sleep schedule, as it was highly variable. Leia took
prescription sleep medication before the study was initiated and she desired to discontinue them.
Baseline data were collected while she was using medication, and continued to be collected for
13 days after her last dose (the medication clears from a person’s system after 7 days).
Luke. Luke was an alumnus of the university. He was a member of the ballroom dance
club and an instructor of the stunt team. Luke aimed to increase his strength and conditioning.
7

2.2 Materials and Measures
Dependent Variables. The main dependent variables were health-related behaviors that
were customized to the unique preferences and desires of the participants. Luke’s primary
measure was the number of workouts (outside of his regular training) he engaged in within a
week. Leia’s specific targets changed throughout the study, according to her preference, but the
overall goal was to establish a more consistent and less variable sleep schedule. Rey also aimed
to improve her sleep. Thus, for Leia and Rey, the main measure was the shortest nightly duration
of sleep in a week.
Strength Test. A brief strength test was conducted for Luke at two points during the
study – both during the intervention phase. The strength test included modified versions of the
push-up (Baumgartner, Oh, Chung, & Hales, 2002) and sit-up tests (Bianco et al., 2015). Luke
was asked to perform as many push-ups and sit-ups as he was capable of doing. No form
requirements were imposed for either task.
Pittsburgh Sleep Quality Index (PSQI). The PSQI (Appendix A; Buysse, Reynolds,
Monk, Berman, & Kupfer, 1989) is a 19-item self-report questionnaire that is used to evaluate an
individual’s sleep quality. The global scores range from 0 to 21, and higher scores are indicative
of poorer sleep quality. The PSQI was administered twice each for Rey and Leia.
2.3 Procedures
Phase 1: Informed Consent and Baseline. The study was explained to participants, and
they were given the opportunity to ask questions. Once the research team ensured that the
participants understood the study and were willing to participate, the participants signed a
consent form. Participants were then asked what specific area they would like to focus on in
terms of health-related behaviors. The person’s baseline rate of engaging in the identified
8

behavior was then assessed. This study utilized a multiple baseline design; as such, the number
of baseline sessions for each participant was dependent on the stability of the data.
Phase 2: Performance Diagnostic Checklist. Each participant was interviewed (see
Appendix B) using a modified version of the PDC. The modifications involved adjusting and
removing items to make them more applicable to the athletic context. The PDC was then scored
and the area that was identified as problematic was addressed in the intervention phase.
Phase 3: Preference Assessment. Preference assessments were conducted with the
participants in order to identify potential reinforcers. This was done through an informal
interview (e.g., asking questions such as “what do you think you would be willing to give
yourself if you succeeded?”). This was conducted several times throughout the intervention.
Participant preference was also taken into account when designing their specific
intervention. Although the techniques used were informed by the PDC, the details (e.g., method
of prompting, reinforcement system, and so on) were decided by the participant and the study
team.
Phase 4: Intervention. Rey. The PDC identified Motivation as the main problematic
area. Thus, a contingency was established such that she would buy a preferred item (swimsuit) if
she slept at least 6.5 hours every night for a week. However, after two weeks, she stated that the
swimsuit was not a consequence that was motivating for her anymore. She mentioned that she
was “competitive with herself” and that she did not want to fail at her goal. Hence, the
reinforcement/feedback system was changed – she was given access to a spreadsheet that
contained a line graph of her performance.
Leia. The PDC identified Motivation as the main problematic area. Thus, a contingency
was established such that Leia had to satisfy certain conditions (e.g., have a nightly sleep
9

duration that fell within a specified range, have a specific weekly average duration) in order to
receive reinforcement (to be able to call home for a specified amount of time). After several
weeks wherein consistent improvement was not seen, another problematic area, Antecedents was
also addressed through the addition of prompts (in the form of nightly text messages). After
several weeks of inconsistent performance, ACT procedures were introduced. Specifically,
values, present moment attention, and acceptance skills were trained using the Body Scan
(Walser & Westrup, 2007) and Matrix (Polk & Schoendorff,, 2014) procedures. Matrix was
trained three times – during the first, third, and fifth week of the ACT phase. Body Scan was
trained once, during the fourth week of the ACT phase.
Luke. The PDC indicated that Motivation was the most problematic area for Luke. Thus,
a contingency was established such that if he were to reach the target frequency of workouts, he
would purchase something for himself. After several weeks of failing to consistently meet the
goal, the second most problematic area, Antecedents was addressed. Luke was asked to schedule
his workouts through his phone calendar app.
Phase 5: Social Validity. The participants were asked to orally answer a questionnaire
(Appendix C) at the end of their participation in the study. The questionnaire assessed the
acceptability of the goals, procedures, and outcomes of the study. They were also given the
opportunity to provide their input regarding what they found effective and ineffective.

10

Chapter 3: Results
Figure 1 shows the results from the PDC. For all three participants, Motivation was
identified as the most problematic area. For Luke, this was followed by Antecedents and
Information, then by Equipment and Processes. For Leia, Motivation was followed by
Equipment and Processes, then by Antecedents and Information. Knowledge and Skills were not
indicated as problematic for Luke and Leia. For Rey, Motivation was followed by Equipment
and Processes, then by Antecedents and Information, then by Knowledge and Skills.
Figure 2 shows the results from the intervention. For all three participants, there was an
increase in level of the target behavior from baseline to intervention.
Rey. At baseline, the average of Rey’s shortest sleep duration was 4.21 hours. Her data
showed a decreasing trend, with little variability. During intervention, the average of her shortest
sleep duration was 5.72 hours. There was moderate variability during intervention.
The first PSQI was administered during baseline, and yielded a global score of 2. The
second PSQI was administered when Rey concluded participation, and yielded a global score of
3.
Leia. At baseline, the average of Leia’s shortest sleep duration was 4.97 hours. There was
no trend, and minimal variability. During the first phase of intervention, the average of her
shortest sleep duration was 4.78 hours. There was no trend, and a large degree of variability.
During the second phase of intervention, the average of her shortest sleep duration was 5.37
hours. There was no trend, and a large degree of variability.
The first PSQI was administered a week after the intervention was started, and yielded a
global score of 13. The second PSQI was administered 7 weeks after the last intervention
session, and yielded a global score of 14.
11

Luke. During baseline, Luke worked out an average of two times per week. His data
showed a decreasing trend, with little variability. During intervention he worked out an average
of 2.75 times per week. There was moderate variability during intervention. Weeks wherein he
was sick for more than one day, weeks wherein he had no access to the gym, and holiday weeks
were not considered, and are left as blank spaces in the graph.
The first strength test was conducted after the 7
th
week of intervention. Luke performed
35 push-ups and 37 sit-ups. The second strength test was conducted when Luke concluded
participation in the study. He performed 46 push-ups and 47 sit-ups. There was a 31% increase in
the number of push-ups, and a 27% increase in the number of sit-ups.
The participants rated the intervention very positively. Rey reported a rating of 5/5, 5/5,
and 3.5/5 for the goals, procedures, and outcomes respectively. Leia reported a rating of 3/5, 4/5,
and 2/5 for goals, procedures, and outcomes respectively. Luke reported a rating of 5/5. 4/5, and
5/5 for the goals, procedures, and outcomes respectively.

12

Chapter 4: Discussion
Overall, the results suggest that the PDC was able to identify putative barriers for each
participant to engage in their desired health-related behaviors. Furthermore, addressing the
barriers identified by the PDC resulted in increased performance in the area of interest. This
study demonstrates that the PDC may be valid in settings outside of the workplace, supporting
the findings of DePaolo and colleagues (2018).
The level of change observed in the dependent variable was not large. However, for all
the participants, engaging in the target behaviors required multiple changes to their lifestyle.
That is, the target behaviors were actually complex repertoires that may take time to develop.
Furthermore, as this study was done in natural settings (with the exception of the study visits),
there were likely multiple real-life extraneous variables affecting the results, and therefore the
small effect may not be surprising.
This study is strengthened by the inclusion of preference assessments in every aspect of
the intervention. While having participants decide the goals and details of their intervention is
not always common in ABA, doing so allowed for social validity to be built in to the study,
rather than hoped for. Allowing participants to re-schedule or participate remotely (phone/video
conference) is also unorthodox. However, doing so was beneficial for two reasons. First, this
allowed there to be continuity in contact, despite the participants’ other commitments. Second,
giving participants freedom to select the mode of delivery of the intervention, as well as the
specific details of the intervention, mirrors real-life coaching settings, thus potentially making
the methods evaluated here easier to apply outside laboratory settings.
While there was improvement in performance for all three participants, there was some
variability, and for one, some ACT procedures were used. It is also possible that since there was
13

no larger, overarching contingency (e.g., no possibility of getting fired as in employment
settings, no possibility of getting removed from the team as in a competitive athletic setting),
there may have been less overall motivation, that is, a smaller overarching establishing operation
to perform the target behavior, compared with previous research on the PDC in employment
settings. Furthermore, the participants were in charge of delivering their own reinforcement, and
it is possible that this was not done with high fidelity. Thus, in situations such as these,
interventions may benefit from the incorporation of values work from the onset. Values
interventions are likely effective because they transform the verbally-mediated positive
reinforcement functions of daily values-oriented behavior, such that automatic positive becomes
a natural consequence for doing what one “values,” so it is not possible to “cheat” and self-
administer reinforcement when one has not engaged in the committed action. Future research
might directly compare experimenter-delivered tangible reinforcement, to participant-delivered
tangible self-reinforcement, to values-based interventions that do not depend on arbitrary
tangible rewards.
The PDC does not have “cutoff” scores or any established way of choosing the most
problematic area. In this study, the most problematic area was identified in terms of percentage
(number of items that were rated as problematic divided by total number of items in that area).
For the sake of parsimony, only the most problematic area was addressed initially. The lack of
clear delineation between problematic and non-problematic areas may have been another factor
that contributed to the inconsistent results. It is possible that having a manualized way of
identifying barriers could produce larger changes in behavior. Furthermore, addressing multiple
areas at once, as opposed to introducing components one at a time, may have strengthened the
14

effect of the intervention. Future research can be done to further systematize the assessment and
the process for choosing between different possible intervention components.
A question that arises from this study is whether similar results can be achieved without
the use of the PDC. Thus, future studies can be conducted to compare interventions based on the
PDC with interventions that were not indicated by the PDC, for example, generic reward-based
interventions for performing target behaviors.
This study had a number of limitations. First, all three participants were from a similar
setting (i.e., members of the university community). Thus, the external validity of these results to
other populations is unknown. Second, ACT was only done with one participant. Thus, there was
no way of evaluating its efficacy with any experimental control. In other words, it is unknown if
ACT produced the change in performance, or if her performance would have improved without
the additional component, since this was not replicated within or across participants. Third, the
use of self-report as the primary measurement system is problematic. A Garmin Vivofit 3 was
initially used to measure engagement in the target behavior. However, there were accuracy issues
(particularly with regards to sleep), participant error (e.g., the participant forgot to wear the
device), and other variables (e.g., skin irritation, issues with syncing the device with the app) that
affected data collection. Thus, the device was used as a secondary measure to corroborate
participant report. However, some concerns about data quality may be alleviated by the inclusion
of additional measures. Fourth, there was a small number of baseline data points, especially for
Rey. However, the need to avoid potential serious consequences of sleep deprivation outweighed
the need for a lengthier baseline period. Finally, there was no formal fading implemented, and no
follow-up data were collected. Thus, it is unknown how durable the behavior change would be.
Anecdotally, Rey stated that the intervention made her more “conscious” about their behavior.
15

Luke stated that he was beginning to establish an effective system that would ensure that he
reached his target for the week.
In conclusion, this study extends previous work done using the PDC into a new area –
self-management of health-related behaviors among athletes. To our knowledge, this is the first
study to use the PDC in self-management contexts (i.e., not within an employment/team setting).
The goal of ABA is to predict and influence behavior, and this is accomplished through
assessment and manipulation of environmental variables. This study opens an avenue for
research and practice in a previously unexplored area.

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Appendix A
Pittsburgh Sleep Quality Index
Instructions: The following questions relate to your usual sleep habits during the past month
only. Your answers should indicate the most accurate reply for the majority of days and nights in
the past month. Please answer all questions.
1. During the past month, what time have you usually gone to bed at night?
2. During the past month, how long (in minutes) has it usually taken you to fall asleep each
night?
3. During the past month, what time have you usually gotten up in the morning?
4. During the past month, how many hours of actual sleep did you get at night? (This may
be different than the number of hours you spent in bed.)
5. During the past month, how
often have you had trouble
sleeping because you…
Not during
the past
month
Less than
once a week
Once or
twice a
week
Three or
more
times a
week
a. Cannot get to sleep within 30
minutes

b. Wake up in the middle of the
night or early morning

c. Have to get up to use the
bathroom

d. Cannot breathe comfortably
e. Cough or snore loudly
f. Feel too cold
g. Feel too hot
h. Have bad dreams
i. Have pain
j. Other reason(s), please describe:
6. During the past month, how
often have you taken medicine
to help you sleep (prescribed or
“over the counter”)?

7. During the past month, how
often have you had trouble
staying awake while driving,

eating meals, or engaging in
social activity?
No
problem at
all
Only a very
slight
problem
Somewhat
of a
problem
A very big
problem
8. During the past month, how
much of a problem has it been
for you to keep up enough
enthusiasm to get things done?

Very good Fairly good Fairly bad Very bad
9. During the past month, how
would you rate your sleep
quality overall?

No bed
partner or
room mate
Partner/room
mate in
another
room
Partner in
same room
but not
same bed
Partner in
same bed
10. Do you have a bed partner or
room mate?

Not during
the past
month
Less than
once a week
Once or
twice a
week
Three or
more
times a
week
If you have a room mate or bed partner,
ask him/her how often in the past month
you have had:

a. Loud snoring
b. Long pauses between breaths
while asleep

c. Legs twitching or jerking while
you sleep

d. Episodes of disorientation or
confusion during sleep

e. Other restlessness while you
sleep, please describe:

Appendix B
Performance Diagnostic Checklist
Antecedents and Information
• Have you received adequate instruction such that you know what to do?
• Can you state the purpose of each task?
• Are there task aids in your immediate environment? Visible while completing the task in
question? Reminders to prompt the task at the correct time/duration?
• Is there anyone present during task completion? (e.g., a supervisor, a coach)
• Are there frequently updated, challenging, and attainable goals set that you are
comfortable with/feel are fair?
Equipment and Processes
• If equipment or materials are required, are they reliable? In good working order?
Ergonomically correct?
• Are the equipment & environment optimally arranged in a physical sense?
• Are there any other obstacles that are keeping you from completing the task?
Knowledge and Skills
• Have you received training on the task? If yes, indicate the training methods: instructions;
modeling; rehearsal
• Tell/show me what you are supposed to be doing and how to do it.
o Examples for health behaviors
▪ Can you tell me what a balanced diet looks like?
▪ Can you tell me what proper sleep hygiene looks like?
▪ Can you demonstrate a plank?

Motivation
• Are there consequences delivered contingent on the task?
o frequency? (list)__________________________________
o immediacy? (list)__________________________________
o consistency/probability? (list)________________________
o positive or negative? (circle one)
o Are there premack reinforcers?
• Do you see the effects of performing task? (How? Natural /arranged)
• Does anyone deliver feedback? (How? Written / verbal; direct /indirect)
• Is there performance monitoring? By whom?
• Is there a response effort associated with performing the task?
• Are there other behaviors competing with the desired performance?
• Why do you care about this behavior?

Appendix C
Social Validity
1: least acceptable; 5: most acceptable
How acceptable were the goals of the
program?
1 2 3 4 5
How acceptable were the procedures of the
program?
1 2 3 4 5
How acceptable were the outcomes of the
program?
1 2 3 4 5

Figure 1. Performance Diagnostic Checklist Results

Figure 2. Intervention Results
Dotted lines: participant selected goals

Abstract (if available)

Abstract Applied behavior analysis methods have often been used in the field of sports. Intervention packages have been created to facilitate acquisition of new skills, improve technique for existing skills, and promote better practice and competition behaviors. Though the efficacy of ABA intervention techniques has been demonstrated multiple times, there is a paucity of research regarding assessment in sports. The Performance Diagnostic Checklist (PDC) is an assessment tool often used in organizational settings to identify barriers to efficient performance. This study evaluated the utility of the PDC for improving health-related behaviors among athletes. Using a multiple baseline design, interventions based on the PDC were evaluated with two students and one alumnus at a university. Results were mixed but overall, there was an increase in the target behavior chosen by the participants upon implementation of the intervention.

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Asset Metadata

Creator Tan, Isabella Maria Camello (author)

Core Title Behavioral coaching for athlete health behaviors

School College of Letters, Arts and Sciences

Degree Master of Science

Degree Program Applied Behavior Analysis

Publication Date 04/08/2020

Defense Date 01/22/2020

Publisher University of Southern California (original), University of Southern California. Libraries (digital)

Tag athlete health,health behaviors,OAI-PMH Harvest,Performance Diagnostic Checklist

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Tarbox, Jonathan (committee chair), Cameron, Michael (committee member), Manis, Frank (committee member)

Creator Email isabelct@usc.edu,isabellamariatan@gmail.com

Permanent Link (DOI) https://doi.org/10.25549/usctheses-c89-280496

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Document Type Thesis

Rights Tan, Isabella Maria Camello

Type texts

Source University of Southern California (contributing entity), University of Southern California Dissertations and Theses (collection)

Access Conditions The author retains rights to his/her dissertation, thesis or other graduate work according to U.S. copyright law. Electronic access is being provided by the USC Libraries in agreement with the a...

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