Objective Dynamic and 3D Knee Assessment Medical Device to Improve Recovery and Accelerate Return to Readiness in Service Members With Knee Pain
Phase: NA
Conditions: Patellofemoral Pain, Patellofemoral Pain Syndrome
Sponsor: Womack Army Medical Center

Research Title: Objective Dynamic and 3D Knee Assessment Medical Device to Improve 
Recovery and Accelerate Return to Readiness in Service Members with Knee Pain 
NCT Number: 06517056 
Document Date: 2/10/2025 

EIRB Protocol Template (Version 1.9)
1.0
General Information
*Please enter the full title of your study:
Objective Dynamic and 3D Knee Assessment Medical Device to Improve Recovery and 
Accelerate Return to Readiness in Service Members with Knee Pain
 
 
*Please enter the Protocol Number you would like to use to reference the protocol:
EMOVI
* This field allows you to enter an abbreviated version of the Protocol Title to quickly identify 
this protocol.
 
 
Is this a multi-site study (i.e. Each site has their own Principal Investigator)?
Yes
 
 
Does this protocol involve the use of animals?
Yes
No
 
 
2.0
Add Site(s)
2.1 List sites associated with this study:
Primary 
Dept?
Department Name
P and R - Womack Army Medical Center (WAMC)
 
3.0
Assign project personnel access to the project
3.1 *Please add a Principal Investigator for the study:
 
Goss, Donald Lee, PhD, PT
Select if applicable
Student
Site Chair
Resident
Fellow
 
3.2 If applicable, please select the Research Staff personnel:
 
A) Additional Investigators
Maldonado, Carlos J, PhD 
 Associate Investigator
Rochester, Kelsey Lee 
N

 Associate Investigator
Tucker, Caitlin Johanna 
 Associate Investigator
B) Research Support Staff
Lucio, Whitley B 
 Non-engaged Administrator
Ory, Rian Lyndzie, MS 
 Non-engaged Administrator
3.3 *Please add a Protocol Contact:
 
Goss, Donald Lee, PhD, PT 
Rochester, Kelsey Lee 
Tucker, Caitlin Johanna 
The Protocol Contact(s) will receive all important system notifications along with the Principal 
Investigator. (i.e. The protocol contact(s) are typically either the Protocol Coordinator or the 
Principal Investigator themselves).
3.4 If applicable, please select the Designated Site Approval(s):
 
Add the name of the individual authorized to approve and sign off on this protocol from your Site 
(e.g. the Site Chair).
4.0
 
Project Information
4.1  
What department(s) will be associated with this protocol?
* 
Physical Therapy
4.2  
Is the IRB of record for this study an IRB/HRPP that does NOT use EIRB? If Yes, complete the 
* 
application according to the IRB/HRPP Determination.
If your Projects or Protocols are under the oversight of another IRB that does use EIRB, stop this 
submission and contact the core site and request an invitation as a performing site.
If your Project or Protocol is now being submitted for the first time to an IRB that does use EIRB, 
continue with this application and answer the questions to be reviewed by the IRB.
Answering yes means the board of record is an IRB that does NOT use EIRB.
  Yes   
  No
4.3  
Is this protocol research, expanded access, or humanitarian use device?
* 
 Yes   
 No
4.4  
 What type of protocol is this?
*

Behavioral Research
Biomedical Research
Clinical trial (FDA regulated)
Educational Research
Expanded Access
Humanitarian Use Device (HUD)
Psychosocial Research
Oral History
Other
4.5  Are you conducting this project in pursuit of a personal degree?
  Yes   
  No
4.7  
Is this human subjects research? (As defined by 32 CFR 219) 
* 
   Human subject means a living 
individual about whom an investigator (whether professional or student) conducting research: 
   (i) Obtains information or biospecimens through intervention or interaction with the individual, and 
uses, studies, or analyzes the information or biospecimens; or 
  (ii) Obtains, uses, studies, analyzes or generates identifiable private information or identifiable 
biospecimens.  
 Yes   
 No
4.8  
 Do you believe this human subjects research is exempt from IRB review?
*
  Yes   
  No
5.0
 
Personnel Details
5.1  Does the Principal Investigator have a Permanent Change of Station (PCS) Date or Estimated 
Institutional Departure Date (EIDD)?
  Yes   
  No
5.2  List any Research Team members without EIRB access that are not previously entered in the protocol:
No records have been added
5.3  Are any Contractors or Subcontractors involved in this study? If yes, please list them and describe their role.
 Yes   
 No
Name:
(Last, First, M.I.)
Rochester, Kelsey 
L.
Role on Protocol:
Phone Number:
910-907-8531
Email Address:
kelsey.l.rochester.
ctr@health.mil
Associated 
Institution:
Geneva Foundation

Associate 
Investigator
Name:
(Last, First, M.I.)
Tucker, Caitlin J.
Role on Protocol:
Associate 
Investigator
Phone Number:
910-907-8531
Email Address:
caitlin.j.tucker.
ctr@health.mil
Associated 
Institution:
Geneva Foundation
Name:
(Last, First, M.I.)
Goss, Don
Role on Protocol:
Principal 
Investigator
Phone Number:
910-907-8531
Email Address:
donald.l.goss.
ctr@health.mil
Associated 
Institution:
Geneva 
Foundation
5.4  
Will you have a Research Monitor for this study?
Yes 
No 
N/A 
6.0
 
Data/Specimens
6.1  Does the study involve the use of existing data or specimens only (no interaction with human 
subjects)?
  Yes   
  No
7.0
 
Funding and Disclosures
7.1  Source of Funding:
Funding Source
Funding Type
Amount
:
Military Operational 
Medicine Research 
Program (MOMRP) 
(JPC-5)
:
Research 
Development 
Testing and 
Evaluation (RDT&E) 
funds
766000
Total amount of funding:
766000

7.2  Do you or any other Investigator(s) have a disclosure of a personal interest or financial nature 
significant with sponsor(s), product(s), instrument(s) and/or company(ies) involved in this study?
  Yes   
  No
All personnel engaged in research must complete and attach a Conflict of Interest (COI) form.
8.0
 
Study Locations
8.1  Is this a collaborative or multi-site study? (e.g., are there any other institutions involved?)
 Yes   
 No
8.2  Study Facilities and Locations:
Institution Site Name
Site Role
FWA or DoD 
Assurance 
Number
Assurance 
Expiration 
Date
Is there an 
agreement?
IRB Reviewing 
for Site
Army
Tripler 
Army 
Medical 
Center
Performance 
site
FWA00003575
05/20
/2027
:
IAIR
:
NMCP 
IRB
Army
Womack 
Army 
Medical 
Center
Lead site
:
CRADA
:
NMCP 
IRB
Other:
Other 
Institution Site
Site Role
FWA or DoD 
Assurance 
Number
FWA or DoD 
Expiration Date
Is there an 
agreement?
IRB Reviewing 
for Site
No records have been added
8.3  Are there international sites?
Attach international approval documents, if applicable, when prompted. Note: Ensure local 
research context has been considered
  Yes   
  No
8.4  Is this an OCONUS (Outside Continental United States) study?
  Yes   
  No
Select  the area of responsibility:
Have you obtained permission from that area of responsibility? (This is a requirement prior to 
study approval)
  Yes   
  No

9.0
 
Study Details
9.1  Key Words:
Provide up to 5 key words that identify the broad topic(s) of your study
Knee pain
Biomechanics
Kinematics
Military
Return to duty
9.2  Background and Significance:
Include a literature review that describes in detail the rationale for conducting the study. Include 
descriptions of any preliminary studies and findings that led to the development of the 
protocol.  The background section should clearly support the choice of study variables and 
explain the basis for the research questions and/or study hypotheses.  This section establishes 
the relevance of the study and explains the applicability of its findings
Physical training and sports-related activities account for 50-90% of 
injuries in the military, while almost half (i.e., 45%) of these injuries are 
due to running activity (Hauret et al., 2015). Daily training, particularly 
for soldiers serving in combat, often consists of high volumes of 
distance running and/or carrying heavy loads (Jones & Hauschild, 
2018). Although there are numerous pathologies associated with 
running, the knee is the most frequently injured joint (Hauret et al., 
2015). Specifically, patellofemoral pain syndrome (PFPS) is the most 
common running-related pathology, as it accounts for 16-21% of all 
running- related injuries (Molloy et al., 2020). The high incidence of 
patients with residual symptoms and chronic deficits suggests that there 
are significant gaps in the way service members with PFPS are 
managed.
With the lack of validated objective functional assessment tools to 
support clinical decision, health care providers (HCPs) must rely on 
subjective visual assessment of the knee movement to formulate a plan 
of care. The accuracy and reliability of observational gait analysis is 
notoriously poor, as even experienced examiners using videotape 
analysis reported only poor to moderate reliability. While current 
diagnostic modalities (e.g., X-ray, MRI) providing information about 
structure in static, non-load-bearing and non-functional conditions, are 
useful to rule out red-flag conditions (e.g., fractures, bony 
abnormalities), they demonstrate poor correlation with PFPS symptoms 
and limitations to guide HCPs in personalized treatment interventions. 
Objectively quantifying the mechanical function of the knee joint and 
identifying the underlying biomechanical causes of PFPS are necessary 
to provide effective and efficient personalized therapeutic interventions. 
It is important to mention that objective functional data already 
demonstrated its value in a civilian population with knee osteoarthritis 
and after knee replacement surgery.
To benefit the military population, biomechanical assessment tools to 
identify root causes of PFP on an individual patient level must be useful 
in garrison, deployed, and other austere settings. Robust gait 

laboratories exist in the MHS, but they are not practical to evaluate 
routine knee conditions. In fact, the use of these facilities for clinical 
care is not feasible as they are expensive, scarcely located at only a 
few key military treatment facilities (MTFs), time consuming and lack a 
method or providing clinical interpretation of findings at the point of care 
(Mukaino et al., 2018; Simon, 2004). 
To address this gap in biomechanical and diagnostic testing for PFP, 
we are proposing to use a validated objective functional assessment of 
the knee at the point of care in military personnel. This testing is known 
as a ‘Knee Kinesiography” exam which accurately and objectively 
assess the knee function during weight-bearing activity. This 
examination includes the use of the KneeKG® system (Emovi Inc., 
Canada – FDA cleared), which has been validated against traditional 
gait laboratories to objectively measure 3D knee movement through 
biomechanical markers linked to knee pathologies (Lustig et al., 2012). 
A Knee Kinesiography exam enables HCPs to provide participants with 
immediate diagnostic information and design intervention strategies to 
address the identified biomechanical deficits. Knee joint kinematics are 
calculated during a 45-second bout of treadmill walking and 
biomechanical deficiencies are automatically detected and flagged in an 
instant report. These biomechanical markers of abnormal function 
consist of those specifically identified as having a causative or 
associative role in PFPS, including altered tibiofemoral rotation (Salsich 
et al., 2007), knee valgus collapse (Tibiero et al., 1987; Powers et al., 
2003), decreased knee flexion during loading (de Oliveira Silva et al., 
2015), and others. The exam takes 10-15 minutes to complete.
The HCP can then design a personalized home exercise program 
guided by this information and an application with detailed validated 
exercises targeting the different biomechanical markers.
Recent results confirmed that targeted exercises based on the Knee 
Kinesiography exam can also improve biomechanical markers 
compared to standard care for knee osteoarthritis (Cagnin et al., 2019). 
Therefore, there is interest to assess the value in adding a knee 
kinesiography exam in the management of PFP.
9.3  
Objectives/Specific Aims/Research Questions:
Describe the purpose and objective(s) of the study, specific aims, and/or research questions
/hypotheses
The purpose of this study is to assess the effectiveness of using a 3D 
medical assessment device versus usual care to help guide clinical 
decisions about the management of PFP. The objective is to determine 
if gathering objective biomechanical data from a three-dimensional (3D) 
motion capture device leads to more precise and optimal care, 
ultimately improving physical function and other outcomes compared to 
participants who receive routine care that is not guided by information 
from this device.

Specific Aim 1: Test the effectiveness of rehabilitation guided by the 
KneeKG functional assessment device for improving the primary 
outcome of PROMIS Physical Function at 3 months compared to usual 
care.
Hypothesis 1: We hypothesize that participants that receive care 
guided by the KneeKG motion capture device will have significantly 
greater improvements in physical function compared to participants that 
receive usual care.
Specific Aim 2: Test the effectiveness of rehabilitation guided by the 
KneeKG motion capture device for improving the secondary outcome 
(PROMIS Pain Interference, Anterior Knee Pain Scale, Global Rating of 
Change, Perceived Military Readiness) at 3 months compared to usual 
care that is not informed by KneeKG data.
Hypothesis 2: We hypothesize that participants that receive care 
guided by the KneeKG motion capture device will have significantly 
greater improvements in physical function and accelerate their return to 
readiness compared to participants that receive usual care.
Specific Aim 3: Assess how well treatment provided in the informed by 
group addressed specific biomechanical impairments identified by the 
KneeKG. The treatment effectiveness will be assessed by a linear 
mixed effects model to analyze the between-group difference in all 
secondary outcomes at 3 months. 
Specific Aim 4: Conduct a qualitative assessment of acceptability, 
feasibility, and utility of the KneeKG device from physical therapists 
practicing in this setting. This will help summarize perceptions about 
value and characterize best-use practices.
9.4  Study Design:
Describe study design in one to two sentences (e.g., prospective, use of existing records/data
/specimens, observational, cross-sectional, interventional, randomized, placebo-controlled, 
cohort, etc.). Specify the phase – Phase I, II, III, or IV – for FDA-regulated investigational drug 
research
This is a randomized clinical trial investigating the use of the Emovi Knee Kinesiography 
information in the treatment of anterior knee pain in physical therapy.
9.5  Target Population:
Describe the population to whom the study findings will be generalized
Active duty service members age 18-50 complaining of atraumatic anterior knee pain
9.6  Benefit to the DoD:
State how this study will impact or be of benefit to the Department of Defense
Patellofemoral pain syndrome accounts for approximately 16-21% of running-related injuries 
across the military (Molloy et al., 2020). If this method of knee assessment proves to be 
beneficial, results and best practices could be shared across the DoD in an effort to improve 
management of patellofemoral pain in this setting.

10.0
 
Study Procedures, Data Management, and Privacy
10.1  Study Procedures:
Describe step-by-step how the study will be conducted from beginning to end
Participants will be recruited from primary care and physical therapy clinics at 
participating sites. Authorized study personnel will search electronic medical 
records (Genesis) to identify potential study participants diagnosed with knee pain. 
After consent and enrollment, participants will complete baseline measures and 
then receive a Knee Kinesiography exam.  The participant will be entered into the 
KneeKG system using a unique participant identifier. After the knee kinesiography 
exam with the KneeKG, participants will be randomized 1:1 into one of two 
different treatment arms: 1) KneeKG informed care or 2) usual care without any 
information from the KneeKG.
Knee Kinesiography Exam with KneeKG:
Knee mechanics during gait is assessed with a Knee Kinesiography exam. The 
participant will walk for 5 minutes on a commercial treadmill at their comfortable 
speed. Three-dimensional (3D) knee kinematics are captured on each leg using 
the KneeKG system (Emovi, Canada). With this validated FDA cleared medical 
device, there is an accurate quantification of specific knee biomechanical markers 
during gait in a clinical setting. There will be two 45-second trials to electronically 
capture the data which is immediately accessible through automatic reports. 
Biomechanical markers captured include but are not limited to varus/valgus 
alignment at stance, varus/valgus alignment at heel strike, knee flexion angle at 
heel strike, total knee excursion in sagittal plane, tibial rotation at heel strike and 
throughout gait cycle. The entire procedure will take approximately 15-20 
minutes.   This procedure will occur at baseline and also again at 4 and 12 weeks.
Randomization:
Participants will be randomized using an electronic random generator in RedCap.
The sequence will be stratified by sex and by acuity (≤ 1 months vs 2 or more 
months) to ensure equal allocation between groups. 
Blinding:
Due to the nature of the intervention, it will not be possible to blind the therapists 
delivering the intervention. However, therapists delivering usual care will not be 
provided the KneeKG data. The participants will be blinded to their assigned 
treatment group.
Treatment 1: Care informed by use of the KneeKG device.
Participants in this group will receive care guided by the impairments identified 
with the KneeKG. The KneeKG exam results in recommended exercises that target 
the specific biomechanical impairments identified. The exercises and dose given to 
the participant will be based on what the KneeKG device recommends after the 
exam. The participant will be seen twice a week for 4 weeks. 
Treatment 2: Usual Care.
Participants in this arm will have their KneeKG data captured, but this information 
will not be provided to the physical therapist to inform their care. Instead, physical 
therapists will deliver care as they normally do in routine clinical practice. 
Recommended treatment will be for 8 sessions, twice a week.
Questionnaires:
Participants will complete questionnaires at baseline, 4 weeks, and 12 weeks. All 
questionnaires will be administered using REDCap. All REDCap data will be labeled 
using a unique participant identification number. Please see the next section for a 
detailed description of the data collection measures utilized in this study.

1.  
2.  
Treatment Log:
Participants will complete a treatment adherence log to turn in at the end of the 
study. The log will be provided as a physical copy and will be labeled using a 
unique participant identification number after it has been returned to the study 
team.
Participant Withdrawal: 
Participants may withdraw their consent at any time. Participants can also be 
withdrawn by the PI if they fail to adhere to the protocol and/or treatment plan. If 
a participant "no-shows" two consecutive appointments, or a total of three 
"no-shows" during the 4wk treatment plan, the PI will withdraw the participant 
from the study. The participant will be contacted to let them know that they are no 
longer eligible for the study. 
10.2  Data Collection:
Describe all the data variables, information to be collected, the source of the data, and how the 
data will be operationally measured.
W0 W4 W12
Knee Kinesiography exam
 X
X
X 
Patient-reported outcome measures (PROMS)
PROMIS  
Pain interference domain
Physical function domain
Anterior knee pain scale
X 
 X
 X
Global Rating of change scale
X 
X 
Self-reported Readiness to RTD questionnaire
X 
 X
X 
Treatment Adherence Activity Log
 X
X 
Provider Satisfaction Questionnaire
X 
Total lost duty days (Self-reported Readiness to RTD questionnaire 5a)
X 
The KneeKG exam will produce two reports, Biomechanical Markers and Kinematic Profile. 
The Biomechanical Markers report will contain the following variables: 
Medial compartment and femoparatellar compartment: varus thrust during 
loading, varus static functional lower limb alignment, varus alignment at 
initial contact, varus alignment during stance, and valgus thrust during 
loading.
Lateral compartment and femoropatellar compartment: valgus thrust 
during loading, valgus functional lower limb alignment, valgus alignment at 
initial contact, and valgus alignment during stance. 
Femoropatellar compartment: dynamic knee contracture in flexion at heel 
strike and external tibial rotation at initial contact.
General: knee in extension at initial contact, limited flexion excursion 
during loading, limited extension movement during stance, internal tibial 
rotation movement during loading, tibia internally rotated in relation to the 
femur during loading. 
The Kinematic Profile report will contain the following movement graphs:
flexion/extension during loading, stance, push off, and swing phases of 
movement.
adduction (varus)/abduction (valgus) during loading, stance, push off, and 
swing phases of movement.

external/internal tibial rotation during loading, stance, push off, and swing 
phases of movement. 
anterior/posterior tibial translation during loading, stance, push off, and 
swing phases of movement. 
The Patient-Reported Outcomes Measurement Information System (PROMIS) asks 
participants about their pain, functional ability, and symptoms. PROMIS is designed as a 
health-focused rather than a disease-focused measurement system (Evans et al., 2018). 
We will focus on the Pain Interference and the Physical function domains since PFPS is 
known to limit function during daily and sports & recreation activities. PROMIS is an 
efficient and reliable tool for patients with patellofemoral malalignment (Carender C.N. et 
al., 2019) and it will be the primary outcome. 
Anterior knee pain scale is a 13-item more specific questionnaire related to PF pain which 
will allow to assess pain and symptoms during specific loading-activities. (Kujala et al., 
1993). 
Self-reported Readiness to RTD questionnaire consists of three questions to assess 
perceived readiness to RTD. 
Service members will complete an activity log to document treatment recommendations 
received and the actual list of followed treatments to monitor adherence. If home 
exercises are prescribed, the member will be required to document the nature and 
frequency of the exercises performed. 
Provider Satisfaction Survey will be used to measure patient satisfaction with quality of 
physical therapy care.
Lost duty days will be tracked in e-Profile by research physical therapists and with Self-
reported Readiness to RTD questionnaire 5a.
Demographic data will be collected verbally by the person obtaining consent. The 
researcher will collect Name, Date of Birth, DOD ID#, Email Address, Phone Number, Sex, 
Ethnicity, Height, Weight, and Side of Knee Pain. This information will be stored in the 
Master Log. 
10.3  At any point in the study, will you request, use, or access health information in any form, including 
verbal, hard copy and electronic?
 Yes   
 No
10.4  Review the definitions below and respond to the following two questions.  If you are not sure of the 
answers, email 
 for assistance.
DHA.PrivacyBoard@mail.mil
   The 
 is 
Military Health System (MHS)
defined as all DoD health plans and DoD health care providers that are organized under the 
management authority of, or in the case of covered individual providers, assigned to or employed by, 
  
the Defense Health Agency (DHA), the Army, the Navy, or the Air Force  
 
MHS workforce members
are employees, volunteers, trainees, and other persons whose conduct, in the performance of work 
  
for the MHS, is under the direct control of the MHS, whether or not they are paid by the MHS.  MHS 
 are persons or entities that provide a service to the MHS and require protected 
business associates
health information (PHI) to provide the service.
Are you an MHS workforce member?
Yes, I am an MHS workforce member 
No, I am not an MHS workforce member 
10.5  Have you consulted with an MHS data expert to determine the data elements required for your study?
Consulting with a data expert often saves time later in the compliance process because the data 
expert can advise on the data available in the numerous MHS information systems, the quality of 
that data and the methods for encrypting and collapsing data.  To schedule a consult with an 
MHS data expert, send an email to: (
)
DHA.PrivacyBoard@mail.mil
Yes, then complete the questions below according to the data consult 
No, then complete the questions below according to the best of your knowledge 
10.6  Indicate how you will request data from the MHS.  Select all that apply.

Talking with MHS health care providers or MHS health plans about specific research 
participants
Obtaining MHS hard copy records specific to research participants
Obtaining data from an MHS information system(s)
10.7  If you are obtaining data from an MHS information system(s), indicate whether you plan to receive a 
data extract or whether you plan to access an MHS information system directly to create a data set.
A data extract is when the MHS or a contractor provides the data set directly to the 
researcher.  When receiving a data set through data extract, the researcher may indicate 
whether the data elements should be provided as is, encrypted or collapsed.  In contrast to a 
data extract, access to an information system means that the researcher may directly access an 
MHS information system and create a data set for the research study
Data Extract
Access
10.8  Do you intend to request de-identified data from the MHS in your research study? 
There are different two methods for de-identifying data pursuant to HIPAA:
1) Safe Harbor Method: Removing all of the identifiers listed in Table 1 below, provided that the 
researcher does not have actual knowledge that the remaining data can be used alone or in 
combination with other information to identify the individual who is the subject of the information
2) Statistical Method: An expert, with appropriate knowledge of and experience with generally 
accepted statistical and scientific principles and methods for rendering information not 
individually identifiable, determines that the data is not individually identifiable
  Yes   
  No
10.9  Indicate the MHS information system(s) from which you will seek to obtain data
If you do not know which system(s) contains the data elements you need, refer to the Guide for 
DoD Researchers on Using MHS Data or request guidance from an MHS data expert at: DHA.
.
PrivacyBoard@mail.mil
 
Below is a list of commonly used MHS systems. If the system from which you seek to obtain 
data is not listed below, list the name of the system in the “Other MHS Systems” category below
PHI Systems:
MHS Information System
Requesting Data
:
MHS Genesis
:
No
PII-Only Systems:
MHS Information System
Requesting Data
No records have been added
De-Identified Data & Other Systems:
Information System
Requesting Data
No records have been added
10.10  Do you intend to merge or otherwise associate the requested data with data from any sources 
outside of the MHS, including other DoD systems that are not part of the MHS?
Yes, will merge data  
No, will not merge data 

10.11  Indicate the data elements about research participants or relatives, employers, or household 
members of the research participants that you will request from MHS hard copies or from MHS 
information systems. 
If you will merge data, also indicate non-MHS data elements about research participants or 
relatives, employers, or household members of the research participants that you will have access 
to in any form or medium.
Direct and 
Indirect 
Identifiable Data 
Elements
DHA Hard 
Copies
DHA Data 
Elements 
to be 
Accessed
DHA Data 
Elements 
Verbal
Extracted 
DHA Digital 
Data
Downloaded 
DHA Digital 
Data
Non-DHA 
Hard 
Copies or 
Digital
1.  Names 
2.  Postal 
address with 
only town, 
city, state, 
and zip code 
3.  Postal 
address with 
all geographic 
subdivisions 
smaller than 
state, 
including 
street 
address, city, 
county, 
precinct, zip 
code and their 
equivalent 
geocodes, 
except for the 
initial three 
digits of a zip 
code if, 
according to 
the current 
publicly 
available data 
from the 
Bureau of 
Census: 1) 
the 
geographic 
unit formed by 
combining all 
zip codes with 
the same 
three initial 
digits contains 
more than 
20,000 
people; and 2) 
the initial 
three digits of 
a zip code 
from all such 
geographic 
units 
containing 
20,000 or 

fewer people 
is changed to 
000
4.  Dates 
including all 
elements 
(except year) 
directly 
related to an 
individual, 
including 
birthdate, 
admission 
date, 
discharge 
date, and date 
of death 
5.  Ages over 
89 and all 
elements of 
dates 
(including 
year) 
indicative of 
such age, 
unless you will 
only request a 
single 
category of 
“age 90 or 
older” 
6. Telephone 
Numbers
7.  Fax 
Numbers 
8.  Email 
Addresses
9.    Social 
Security 
Numbers
10.   Medical 
Record 
Numbers 
(MRN) 
(including 
record ID)
11.   Health 
Plan 
Beneficiary 
Numbers  
(including 

DEERS ID, 
Electronic 
Data 
Interchange 
Personal 
Identifier 
(EDIPI) or 
Number 
(EDIPN))
12.   Account 
Numbers 
13.   Certificate
/License 
Numbers 
14.   Vehicle 
identifiers and 
serial 
numbers, 
including 
license plate 
numbers 
15.   Device 
identifiers and 
serial numbers 
16.   Web 
Universal 
Resource 
Locators 
(URLs) 
17.   Internet 
Protocol (IP) 
address 
numbers 
18.   Biometric 
identifiers, 
including 
finger and 
voice prints 
19.   Full-face 
photographic 
images and 
any 
comparable 
images
20.   Any 
other unique 
identifying 
number, 

characteristic, 
or code 
(including non-
military 
provider IDs)
21.   Free Text 
Fields
If you are obtaining SSNs, provide a justification as to why and explain why a substitute cannot 
be used.
Due to guidelines stated within DoDI 1000.30, Reduction of SSN Use within DoD, the reduction 
or elimination of SSN usage must occur wherever possible. If SSNs are required to complete the 
project, the PI must provide a justification and explanation as to why a substitution cannot be 
used.
For example:
• If alternatives to SSN (e.g., EDIPNs or pseudo person IDs) are sufficient in other instances, 
will those alternatives to SSN usage be sufficient to respond to Congressional inquiries and
/or Senior DoD stakeholders inquiries?
• Are alternatives to SSN used first?
• Are those alternatives to SSN insufficient to combine data from multiple data sources? Is 
the issue that some individuals do not possess alternatives ID numbers and SSN is the only 
way to identify them?
a. Will you receive or obtain health information?
Note: If you indicate you are not receiving health information, the answer 
must be consistent with the DHA data source. For a non-health 
information data request, if you are a non-MHS employee or non-MHS 
business associate, you may not access an information system that has 
PHI or LDS. For both MHS and Non-MHS employees and MHS business 
associates, you may 
 include data elements in the above table on: 
NOT
1)  lines 10 or 11, 2) line 21 if the free text field comes from a PHI or LDS 
system, and 3) lines 12, 13, or 18 if the account numbers, certificate and 
license numbers, biometric data, or any other data elements are health 
information created or received by an MHS health care provider, health 
plan, or business associate in relation to the physical or mental health or 
condition of an individual or payment for health care.
Yes, I will receive or obtain health information 
No, I will not receive or obtain health information 
b. If no data elements were checked in the above table, is it possible that the requested DHA 
data is or will be identifiable because of any unique data elements, triangulation, or small cell 
size?  
Data elements were checked in the above table, STOP HERE.
NOTE: A unique data element includes any unique features that alone are not identifiable but 
that could be used to identify an individual within the context of other information, such as any 
type of code (such as diagnosis or procedural), rank of general or admiral, gender, or race. 
Triangulation means using different data elements that when combined can be used to identify 
an individual, such as including the above lists of unique data elements in a data set. 
Determining whether an individual is identifiable through triangulation requires consideration of 
all data elements in combination. Within the military, the use of rank and/or diagnosis code, 
procedural codes, or any other code that changes on a predictable basis, increases the possibility 
of identification. Small cell size means that there is only a small number of eligible individuals 
that satisfy the category description. Department of Defense Manual 6025.13, Medical Quality 
Assurance and Clinical Quality Management in the Military Health System MHS, provides that the 
threshold for de-identifying data within the MHS requires a cell size of three, but also states that 
the de-identification standards must meet the DoD implementation of the HIPAA Privacy Rule. 

Centers for Medicare and Medicaid also gives guidance on small cell size stating that no data cell 
less than 11 may be published or displayed. However, the Office for Civil Rights’ OCR, which is 
the official regulatory office for the HIPAA Privacy Rule, provides that OCR does not designate a 
universal value for small cell size in accordance with the de-identification standard; instead, the 
cell size should be set at a level that is appropriate to mitigate risk of identification by the 
anticipated recipient of the data set. This means that a cell size of 3 or 11 may not meet the 
HIPAA Privacy Rule requirements if the cell size level does not appropriately mitigate risk of 
identification by the anticipated recipient of the data set.
Note: If dates are altered as a means of de-identifying the data, diagnosis and 
procedural codes need to be rolled-up or collapsed. If dates are provided “as time 
between events,” the roll-up is not necessary.   
Yes, the DHA data will become identifiable
No, the DHA data will not become identifiable
10.12  Do you believe it is possible for the MHS data to become identifiable because of triangulation, a 
small cell size, or any unique data element(s)?
Triangulation means using different data elements that are not themselves identifiable but that 
when combined can be used to identify an individual. For example, triangulation would use rank 
and race together to determine the identity of an individual with a particular health condition.
 
Small cell size means that there is only a small number of eligible individuals that satisfy the 
category description. Guidance for acceptable cell size is available from the Centers for Medicare 
and Medicaid Services. For example, the rank category of four star generals with a particular 
diagnosis may be less than 30, so the rank category may need to be expanded to include lower 
ranks.
 
A unique data element includes any unique features that are not explicitly enumerated in the 
categories of data in rows 1 – 20 of the table above (in Section 10.10), but that could be used to 
identify an individual. Unique data elements include characteristics that are not themselves 
identifying, such as the rank of general or admiral, or a race or gender, but within the context of 
other information could be identifiable.
Yes, I believe there is a reasonable possibility the MHS data will become identifiable 
No, I believe there is no reasonable possibility the MHS data will become identifiable 
10.13  Have you completed and uploaded an appropriate HIPAA document ( i.e. HIPAA Authorization will 
be obtained or Waiver/alteration of HIPAA Authorization is being requested)?
Yes 
No 
N/A 
If yes, please check which one.
HIPAA Authorization
HIPAA Waiver (Full or Partial)
Other (please provide copies when uploading Other Study Documents)
10.14  Managing Data (Data Management and/or Sharing Plan) and/or Human Biological Specimens for 
this Study:
Include in this section the plan for acquiring data (both electronic and hard copy), access during 
the study, data/specimen storage and length of time stored, shipment/transmission, and the 
plan for storage and final disposition at the conclusion of the study. Describe any data 
agreements in place for accessing data within and/or outside of your institution (e.g., Data 
Sharing Agreement, Data Use Agreement, Business Agreements, etc.)
Data Capture Methods:
The local study team will collect study data directly from the study participant (in person, over 
the phone, or directly into REDCap), for from the participant’s medical record (i.e., relevant 

medical and treatment history and relevant clinical notes).
REDCap is an encrypted, access controlled, password-protected electronic data capture and 
management system maintained by the Geneva Foundation. No PII will be entered into REDCap.
Participants may also enter study data directly into REDCap using a coded survey link or via a 
tablet provided by the research team. Motion capture data will be recorded directly on the Emovi 
KneeKG system. All information collected through the Emovi KneeKG system will be housed in 
the KneeKG system. All other research data collected on paper, if applicable, will be entered into 
REDCap by the research team.  Other source documents include relevant Kinematic and 
Biomechanical Reports, personalized exercises, and clinical notes which will be printed, redacted, 
and stored in the participant’s research file. Once verified, the paper documentation will be 
securely destroyed. All paper documentation will be kept in a locked, secure cabinet within a 
locked, secure office accessible only by the authorized site research team.
Data Storage & Access:
With the exception of the Informed Consent Document and HIPAA Authorization, and electronic 
master list, all research data (both paper and electronic) will be identified using a unique study 
ID only and not by the participant’s identifiers such as name, date of birth, DoD ID, or other any 
protected identifier.
Paper research forms and source documents will be stored in a locked cabinet inside within a 
locked room, accessible only by local approved research staff designated and authorized by the 
site PI. The coded electronic research data for this study will be stored in REDCap and will only 
be accessible by local research staff designated and authorized by the PI. 
Access to the electronic coded research data will be governed strictly on an individual basis 
within REDCap. Data access and privileges will be clearly delegated, audited, and monitored by 
the core PI. Appropriate data sharing agreements will be in place between the data owner(s) (e.
g. DHA for AHLTA, Genesis) and the Geneva Foundation. 
During data collection, all files containing coded research data will be encrypted, password-
protected, and stored on a secure, HIPAA-compliant computer and file system. This ensures that 
participant confidentiality is protected throughout the study. Such secure file systems are often 
created on department-designated shared drives (intranet) for PII and PHI by the Information 
Management Division (IMD). The electronic master list will be stored separately from the coded 
electronic research data in a secure, password protected Excel spreadsheet on a computer and 
network requiring CAC access. Only approved, local, research staff will have access to the master 
list.
All research data and forms (paper and electronic) will only be accessible by authorized study 
staff, the local IRB, and applicable governmental agencies, in accordance with federal law. These 
duties include ensuring the protection of research participants. The electronic coded research 
data will be maintained indefinitely as described in protocol section 10.15.
After the study closes, de-identified data will continue to be stored in an encrypted, password-
protected format on a secure, HIPAA-compliant system. At the end of the study, the master list 
and any other paper documentation kept throughout the study will be permanently destroyed. At 
this point, the data will be fully de-identified, and there will be no way to re-link the data back to 
individual participants. The de-identified dataset will be securely stored indefinitely for potential 
secondary analyses.
Data Transfer and Security:
At all sites, a site-specific master list will be kept that links the participant (name, DoD ID and 
coded subject identification number). That list will be kept secure and under the purview of the 
site-specific PI, stored on an encrypted computer and in an encrypted and password-protected 
file. If any de-identified study data needs to be transferred to the Core Site, the data will be 
transferred using a DoD-approved Safe File Exchange (SAFE) to the core site’s PI to merge files 
from all sites. DoD-approved SAFE is considered as an encrypted, secure, and preferred for 
sensitive information exchanges. The master list will be destroyed after the study closes, and 
there will be no way to identify individuals in the cohort.
Any de-identified data sharing with organizations outside the DoD (MTEC, MOMRP) will occur 
after appropriate Data Sharing/Use Agreements are approved, ensuring that only coded, non-
identifiable information is exchanged securely.
Managing Data Access:
The study team will access data within the designated MHS systems in a secure, de-identified 
format. The research team will view relevant information directly within the MHS platform to 
maintain confidentiality and comply with data protection protocols. No identifiers (PII/PHI) will be 
recorded, collected, or stored as part of this study, and all access will remain strictly within the 
system.

If follow-up is required for any data clarification, the research team may refer to the master list. 
Prior to analysis, only files containing coded identifiers will be used to ensure that no PHI is 
included in the final dataset. The research staff will strictly maintain the confidentiality of all 
participant information, adhering to established privacy and security protocols.
Nature of Identifying Data:
Timeframes will be requested in reference to the baseline enrollment date, not actual dates. For 
example, the date of appointment will be required initially to determine when the healthcare visit 
is associated with the Knee Kinesiography exam that occurred. However, this data will be coded 
differently in the working spreadsheet. Follow-up appointments will be recorded in days from the 
baseline examination (e.g. +35 or +135, etc.). The exact appointment date will not be included 
in the master list. Analysis of the data will only occur in the coded spreadsheet.
 
Is this a data repository?
  Yes   
  No
10.15  Managing Data (Data Management and/or Sharing Plan) and/or Human Biological Specimens for 
Future Research:
If the study involves collecting, storing, or banking human specimens, data, or documents 
(either by the Investigator or through an established repository) for FUTURE research, address. 
How the specimens/data will be used, where and how data/specimens will be stored (including 
shipping procedures, storage plan, etc.), whether and how consent will be obtained, procedures 
that will fulfill subjects’ request as stated in the consent, whether subjects may withdraw their 
data/specimens from storage, whether and how subjects may be recontacted for future research 
and given the option to decline, whether there will be genetic testing on the specimens, who will 
have access to the data/specimens, and the linkage, the length of time that data/specimens will 
be stored and conditions under which data/specimens will be destroyed.
No human specimens will be collected, banked or stored in this study. 
The electronic master list will be destroyed following the completion of the study; it will be stored 
separately from the coded electronic research data in a secure, password protected Excel 
spreadsheet on a computer and network that requires CAC access and will only be accessible by 
local research staff. The de-identified electronic dataset will be maintained indefinitely (or as long 
as it is practicable to maintain) for possible use in future research. 
Long Term Data Storage & Access: 
The coded electronic research data will be securely transmitted from local study teams to the 
Geneva Foundation via REDCap or the DoD SAFE application (or other comparable safe data 
sharing system implemented by the local site and/or the US Army/DHA). REDCap utilizes Secure 
Sockets Layer (SSL) in addition to other safeguards on its web server to maintain secure 
communication with end-users (see Appendix G). DoD SAFE uses a TLS (Transport Layer 
Security) protocol when files are uploaded and downloaded. Once received, the electronic coded 
research data will be stored within REDCap, an encrypted, access controlled, password protected 
electronic data capture and management system maintained by the Geneva Foundation. Access 
to the de-identified research data will be governed strictly on an individual-by-individual basis 
within the secure electronic data capture and management system. Individual data access as 
well as privileges will be clearly delegated, audited, and monitored by the core PI. Any future 
research using the deidentified data collected in this study will be approved by an Institutional 
Review Board (IRB). Access to the de-identified Emovi KneeKG research data will be governed 
strictly on an individual- by-individual basis by the core PI.
 
Consent for Future Use:
The Informed Consent Form for this research study will state that de-identified research data will 
be maintained indefinitely for possible use in future research. By consenting to participate in this 
research study, participants agree to allow us to maintain their deidentified research data 
indefinitely for possible use in future research.
. 
Is this a data repository?
 Yes   
 No

If Yes, provide the name of the Repository
The Geneva Foundation REDCap
Who will have access to the Repository?
Authorized study personnel
What data type will be stored in the Repository?
Protected Health Information
Limited Data Set
De-identified Data
11.0
 
Statistical/Data Analysis Plan
11.1  Data Analysis Plan and Statistical Considerations:
List the statistical methods to be used to address the primary and secondary objectives, specific 
aims, and/or research hypotheses. Explain how missing data and outliers will be handled in the 
analysis. The analysis plan should be consistent with the study objectives. Include any subgroup 
analyses (e.g., gender or age group). Specify statistical methods and variables for each analysis. 
Describe how confounding variables will be controlled in the data analysis.
The primary outcome is the between-group difference in PROMIS Physical Function T-score at 3 
months. A linear mixed effects model will be used to analyze the between-group differences 
across the various time points (repeated measures). These models are robust for handling 
unbalanced data and can be flexible in accounting for missing data. This will be our primary plan 
for handling missing data, but plan to run sensitivity analysis using multiple imputation (Markov 
chain Monte Carlo with 20 iterations), assuming data is missing completely at random (Little’s 
MCAR Test is not significant). We will report estimated marginal mean T-Scores (e.g. least 
squares mean) with 95% confidence intervals and set statistical significance at P value of <0.05. 
Age, sex and baseline PROMIS Physical Function scores will be added to the model as covariates.
Secondary outcomes that are continuous variables will be analyzed in the same manner. All 
other data collection tools besides PROMIS Physical Function scores are secondary outcomes. 
Non-parametric tests will be used to analyze dichotomous and categorical variables.
Descriptive statistics will be used to examine the distributions of demographic and clinical 
characteristics of the intervention and usual care control group before participant treatment has 
started (pre-treatment data). Means and standard deviations will be calculated for continuous 
variables that are normally distributed. The median and interquartile range will be calculated for 
those showing an asymmetric distribution. For categorical variables, we will use frequency tables 
and proportions. Statistically significant differences between groups will be identified and 
adjustments will be made in all subsequent analyzes to take into account the potentially 
confounding effects of these variables ("potential confounders"). Demographic and clinical pre-
treatment data for participants who completed all follow-up measures and those who dropped 
out during the study will also be compared to assess the possible presence of an attrition bias.
11.2  Sample Size:
A power sample size calculation has been performed to observe a 20-point difference on the 
PROMIS questionnaire with an 80% statistical power (effect size 0.3, SD=10). A total of 149 
patients will be needed, with an equal number of participants allocated to each intervention 
group (i.e., 75). Accounting for a 20% attrition, our goal is to recruit 180 participants for this 
study (both sites included).
11.3  Total number of subjects requested (including records and specimens):
180

11.4  If you are recruiting by study arm, please identify the arms of the study and how many subjects will 
be enrolled in each arm
This will be a two armed randomized clinical trial with 75 participants with knee pain in each 
arm.
11.5  Please provide a justification for your sample size
A sample size calculation has been performed to observe a 20-point difference on the PROMIS 
questionnaire with an 80% statistical power (effect size 0.3, SD=10). The statistical method for 
this power sample size calculation was a linear mixed effects model. A total of 149 
will be needed, with an equal number of participants allocated to each intervention 
participants 
group (i.e., 75). Accounting for a 20% attrition, our goal is to recruit 180 participants for this 
study (both sites included). 
12.0
 
Participant Information
12.1  Subject Population:
The subject population is active duty service members who have been diagnosed with 
patellofemoral pain syndrome (PFPS) at Womack Army Medical Center (WAMC) and Tripler Army 
Medical Center (TAMC).
12.2  Age Range:
Check all the boxes that apply. if the age range of potential subjects (specimens, records) does 
not match the range(s) selected, please specify in the text box.
0-17
18-24
25-34
35-44
45-54
55-64
65-74
75+
18-50
12.3  Gender:
Male
Female
Other
12.4  Special categories, check all that apply
Minors /Children
Students
Employees - Civilian
Employees - Contractor
Resident/trainee
Cadets /Midshipmen
Active Duty Military Personnel

Wounded Warriors
Economically Disadvantaged Persons
Educationally Disadvantaged Persons
Physically Challenged (Physical challenges include visual and/or auditory impairment)
Persons with Impaired Decisional Capacity
Prisoners
Pregnant Women, Fetuses, and Neonates
Non-English Speakers
International Research involving Foreign Nationals - Headquarters Review is necessary
You must also consider the requirements of DoDI 3216.02, Enclosure 3, paragraph 7.e.
12.5  Inclusion Criteria:
Order 
Number
Criteria
1 
Age 18-50
 
2 
Active Duty Service Member stationed at Fort Liberty and Schofield Barracks
 
3 
Diagnosis of patellofemoral pain (ICD-10 codes: M25.2 (pain in unspecified knee), 
M25.561 (pain in right knee), and M25.562 (pain in left knee)
 
12.6  Exclusion Criteria:
Order 
Number
Criteria
1 
Pregnancy
 
2 
Known to be leaving that duty station within next 3 months
 
3 
Concurrent lower limb injuries (examples include but are not limited to ankle 
sprain or HS strain)
 
4 
Previous knee surgery
 
5 
History of traumatic knee injury, such as ligament tear or meniscal tear
 
6 
Presence of rheumatoid or neurological diseases
 
13.0
 
Recruitment and Consent
13.1  Please describe the recruitment process, including how subjects will be identified and selected for 
the study.

Participants will be screened by the research team from those seen in physical therapy and 
primary care clinics.  A record review in Genesis will be completed searching for knee pain 
diagnoses in primary care and physical therapy documentation. We will also accept direct 
referrals from PTs.
13.2  Compensation for Participation:
No
13.3  Please describe the pre-screening process. If no pre-screening, enter Not Applicable in the text editor
Genesis screening knee referrals and visits to physical therapy clinics at Fort Liberty and 
Schofield Barracks.  Participants will be contacted via a phone call and asked if they would like to 
come in and meet with the research team in order to read the consent form and decide if they 
would like to volunteer to participate in the study. This is when the Emovi Sample Interview 
Script will be used. If they choose not to participate, they will receive their normal standard of 
care physical therapy for their knee pain.
13.4  Consent Process:   Revised Common Rule, Section 219.116:  General requirements for informed 
consent, whether written or oral, are set forth in this paragraph and apply to consent obtained in 
accordance with the requirements set forth in paragraphs (b) through (d) of this section. Broad 
consent may be obtained in lieu of informed consent obtained in accordance with paragraphs (b) and 
(c) of this section only with respect to the storage, maintenance, and secondary research uses of 
identifiable private information and identifiable biospecimens.
Are you requesting a waiver or alteration of informed consent?
  Yes   
  No
Please explain the consent process:
The research team will consent participants in a private area. Potential participants will be invited 
into the research office or conference room to meet the research team. We have a planned script 
(Emovi Sample Interview Script) that will be used for recruitment. The research team members 
will explain the study to the subject and offer them a chance to read the consent form. The 
research team will offer to answer any questions the participant has prior to signing the consent 
form. After consent, the baseline data collection will occur. During the consent process, it will be 
made clear to them that they can continue with their standard of care physical therapy treatment 
for their knee pain and choose not to participate in the study.
13.5  DoDI 3216.02 requires an ombudsman to be present during recruitment briefings when research 
involves greater than minimal risk and recruitment of Service members occurs in a group setting. If 
applicable, you may nominate an individual to serve as the ombudsman.
N/A 
Propose ombudsman 
13.6  Withdrawal from Study Participation:
Explain the process for withdrawal and specify whether or not the subjects will be given the 
opportunity to withdraw their data their data/specimens in the event they wish to withdraw from 
the study
Participants may withdraw their consent at any time and stop participating in this research study 
without affecting their eligibility for care or any other benefits to which they are entitled. They 
have the right to withdraw from this study at any time. If they decide to stop taking part in this 
study, they will contact the principal investigator as soon as possible. If this happens, the 
research team will use the Emovi Master Log to identify the data that is associated with the 
participant. Then the team will remove the participant's data from the existing study data.

Participants can be withdrawn by the PI if they fail to adhere to the protocol and/or treatment 
plan. 
14.0
 
Risks and Benefits
14.1  
Risks of Harm:
Identify all research-related risks of harm to which the subject will be exposed for each research 
procedure or intervention as a result of participation in this study.  Consider the risks of breach 
of confidentiality, psychological, legal, social, and economic risks as well as physical risks.  Do 
not describe risks from standard care procedures; only describe risks from procedures done for 
research purposes
The main risk of this study is a potential loss of privacy. The physical risks associated with 
participating in this study are minimal. There is minimal risk of muscle soreness as participants 
complete the walking. However, soreness can be expected during standard rehabilitative care, 
and typically resolves within 2-3 days. There is a small risk that participants may fall during 
treadmill walking.
14.2  
Measures to Minimize Risks of Harm (Precautions, safeguards):
For each research procedure or intervention, describe all measures to minimize and/or eliminate 
risk of harms to subjects and study personnel
We will protect subjects' privacy by labeling exercise programs and information only with a 
unique study ID number, and by keeping the link to these ID numbers in a password-protected 
database on a secure military server which is only accessible by the principal investigator and 
designated research staff using CAC authentication.
The physical risks associated with participation in this study are minimal. To minimize the risk of 
stress fracture the participants’ response to running will be assessed weekly for the first 4 weeks 
and bi-weekly thereafter through individual video follow-ups to minimize this harm.
There are multiple safeguards to help prevent the risk of falling off of the treadmill. On the 
treadmill, participants will wear a safety clip to trigger the emergency stop if needed. 
Additionally, the treadmill has safety guardrails that a participant can grab onto if they lose their 
balance.
Adverse events which are not serious are reported on the Annual Progress Report (APR) during 
the continuing review of the protocol. APR is due in a 12-month cycle, the anniversary month of 
the protocol’s initial approval or due in less than 12-month cycle as determined by the IRB for 
continuing review and approval.
Serious Adverse Events: The PI, within two working days, will report all serious adverse events 
(SAE) occurring in participants. This is accomplished by submitting an adverse event report 
memorandum to the IRB. Additionally, the WAMC HPA will be notified immediately of any 
adverse events. Serious adverse events will be reported even if the PI believes that the adverse 
events are unrelated to the protocol.
14.3  
Confidentiality Protections (for research records, data and/or specimens):

Describe in detail the plan to maintain confidentiality of the research data, specimens, and 
records throughout the study and at its conclusion (e.g., destruction, long term storage, or 
banking). Explain the plan for securing the data (e.g., use of passwords, encryption, secure 
servers, firewalls, and other appropriate methods). If data will be shared electronically with 
other team members/collaborators outside the institution, describe the method of transmission 
and safeguards to maintain confidentiality. Explain whether this study may collect information 
that State or Federal law requires to be reported to other officials or ethically requires action, e.
g., child or spouse abuse
Like many biomedical research protocols considered by IRBs, the protection of confidentiality 
among subjects is a significant concern. In order to protect the confidentiality of all subjects, all 
subjects will be assigned a unique participant identification number upon enrollment. Each 
number assigned will only be used once. All research-related data (both paper and electronic) 
will be labeled using this unique identification number and not by participant name, date of birth, 
DoD ID, or other similar identifier. Consent forms and data collection forms will be stored in 
separate locked filing cabinets in a locked room. 
The master log document linking participant names and their participant numbers will be kept 
secure on a government computer assigned to the PI. The computer is password and CAC-card 
protected, and the system is firewall protected. This document will not be shown to anyone 
except for the investigators in this study or governmental agencies only in accordance with 
federal law. The de-identified spreadsheet data will be password and firewall protected. 
All electronic data will be stored on password secured computers, behind locked doors. Data files 
for this study will be stored on a secure sever with DoD firewalls. Data from this study will be 
transmitted encrypted to only the associate investigators as needed.
Any data submitted to an approved agency for review will be linked only to the participant's 
study number and not the personal identity of the participant (i.e. protected health information 
such as name, address, phone number, etc.) If the data are used in scholarly presentations of 
journal articles, the investigators will protect the anonymity of individual patients and will report 
only aggregate data (e.g. group means) where appropriate. Participants will not be specifically 
identified in any publication or presentation of research results.  
14.4  
Potential Benefits:
Describe any real and potential benefits of the research to the subject and any potential benefits 
to a specific community or society
If the individuals in the research are considered experimental subjects (per 10 USC 980), and 
they cannot provide their own consent, the protocol must describe the intent to directly benefit 
all subjects
Prospective case study participants have experienced positive results.  If improvements are 
observed, these results will be shared with other rehabilitation professionals across the DoD to 
potentially benefit hundreds of thousands of active-duty service members with knee pain.
14.5  
Privacy for Subjects:
Describe the measures to protect subject’s privacy during recruitment, the consent process, and 
all research activities, etc.
Recruitment and consent conversations will take place in a private setting (e.g. closed clinic 
room, investigator's office, etc.) to minimize the potential opportunity to be overheard or 
inadvertently witnessed. Information being collected will be limited to only the minimum amount 
of data necessary to accomplish the proposed research. Additionally, all subjects will be assigned 
a unique participant identifier number upon enrollment in order to protect their privacy. All 

research-related data (both paper and electronic) will be labeled using this unique participant 
identification number and not by participant name, date of birth, DoD ID, or similar identifier. 
Consent forms will be locked in a locked cabinet in a locked office. 
All questionnaires and the Provider Satisfaction survey will be delivered electronically through 
REDCap. Electronic data will be stored in a password protected file on a CAC enabled secure 
drive protected intranet with CAC enabled computers.
14.6  
Incidental or Unexpected Findings:
Describe the plan to address incidental findings and unexpected findings about individuals from 
screening to the end of the subject’s participation in the research. In cases where the subject 
could possibly benefit medically or otherwise from the information, state whether or not the 
results of screening, research participation, research tests, etc., will be shared with subjects or 
their primary care provider. State whether the researcher is obligated or mandated to report 
results to appropriate military or civilian authorities and explain the potential impact on the 
subject
Based on the type of data being collected in this study, the researchers do not anticipate any 
incidental or unexpected findings. No biological specimens are being collected and no genetic 
testing is being completed. In cases where the subject could possibly benefit medically or 
otherwise gain from the study, results will be shared with the subject. The researcher will contact 
the subject and arrange for follow-up care. Unexpected findings or adverse events will be 
reported by the PI within 10 (ten) working days to the Institutional Official through the Human 
Protection Administrator (HPA) and to the IRB through the HPA and directly through EIRB. 
15.0
 
Study Monitoring
15.1  Your study requires either Data and Safety Monitoring Plan (DSMP) or a Data and Safety Monitoring 
Board (DSMB).
DSMP 
DSMB 
Both 
Not Applicable 
16.0
 
Reportable Events
16.1  Reportable Events: Consult with the research office at your institution to ensure requirements are 
met. Describe plans for reporting unexpected adverse events and unanticipated problems. Address 
how unexpected adverse events will be identified, who will report, how often adverse events and 
unanticipated problems will be reviewed to determine if any changes to the protocol or consent form 
are needed and the scale that will be used to grade the severity of the adverse event. 
Consult with the research office at your institution to ensure requirements are met
 
• Describe plans for reporting expected adverse events. Identify what the expected adverse 
events will be for this study, describe the likelihood (frequency, severity, reversibility, short-
term management and any long-term implications of each expected event)
 
• Describe plans for reporting unexpected adverse events and unanticipated problems. Address 
how unexpected adverse events will be identified, who will report, how often adverse events and 
unanticipated problems will be reviewed to determine if any changes to the research protocol or 

consent form are needed and the scale that will be used to grade the severity of the adverse 
event
The principal investigator is the individual who is primarily responsible for the actual execution of 
the clinical investigation. He is responsible for the conduct of the study, obtaining participants' 
consent, providing necessary reports, and maintaining study documents. The Associate 
Investigators will assist the Principal Investigator in these responsibilities. 
The PI will be familiar with all applicable regulations governing research and will adhere to all of 
the requirements outlined in the DOD Assurance and Federal-Wide Assurance granted by the 
Office for Human Research Protections, Department of Health and Human Services. 
The PI will be familiar with all applicable regulations set forth by the NMCP IRB.
As soon and possible, but no longer than three calendar days, events are to be reported to the 
site specific HRPP and NMCP IRB. The PI or designee will report to the site specific HRPP and 
NMCP IRB by email, phone or face-to-face; the HPD will communicate this to the IO and the AIO. 
The PI will upload the report and notice into IRB for the site specific HRPP and NMCP IRB; the 
HPD will facilitate that information through EIRB.
Minor Deviations will be reported to the site specific HRPP and NMCP IRB at the time of 
continuing review or project closure. 
Major Deviations will be promptly reported to the site specific HRPP and NMCP IRB no later than 
5 days. 
Serious Adverse Events: The PI, within three working days, must report all serious adverse 
events (SAE) occuring in participants enrolled at WAMC or TAMC. This is accomplished by 
submitting an adverse event report memorandum to the site specific HRPP and the NMCP IRB. 
Adverse events that are expected and therefore are not UPIRTSOs (to include IND safety 
reports) will be tracked on a log and monitored by the PI. These adverse events will be reported 
to the stie specific HRPP and the NMCP IRB at the annual Continuing Review. 
All UPIRTSOs, UADEs, and SAEs that are unexpected and determined to be at least possibly 
related or definitely related to research participation will be promptly reported by telephone 
757.953.5939 or via email to the group email box: usn.hampton-roads.navhospporsva.list.
 A complete report will follow 
nmcp-usarmy.liberty.medcom-wamc.mbx.hrpp@health.mil
the initial notification withing five (5) business days. 
17.0
 
Equipment/non-FDA Regulated Devices
17.1  Does the study involve the use of any unique non-medical devices/equipment?
  Yes   
  No
18.0
 
FDA-Regulated Products
18.1  Will any drugs, dietary supplements, biologics, or devices be utilized in this study?
Drugs
Dietary Supplements
Biologics
Devices
N/A
18.3  Device Details:

Are device(s) in this research being used in accordance to the approved labeling?
Are device(s) in this research being used in a manner other than its approved labeling?
When adding a device indicate in the details section of the device if the use is either used in 
accordance to the approved labeling or in a manner other than it's approved labeling
View Details
Device Name
Emovi Knee KG 
Manufacturer/Supplier of 
Device
Emovi 
Where will the Devices Be 
Stored
In physical therapy sections locked up 
Will Devices be supplied at no 
Cost
No 
Is this a HUD (HDE)
No 
HDE Number
 
Who holds the IDE
N/A  
IDE details
 
18.4  Reporting Requirements for FDA-regulated research under IND and IDE:
Describe the process for complying with FDA regulatory requirements for adverse event 
reporting and adverse device effects reporting to the sponsor
Research team must report to the manufacturer each adverse experience,as soon as possible but 
no later than 15 calendar days from initial receipt of the information by the Research team.
18.5  Sponsor (organization/institution/company):
N/A
If applicable, provide sponsor contact information:
19.0
 
Research Registration Requirements
19.1  ClinicalTrials.gov Registration:
Registration is not required 
Registration pending 
Registration complete 
“NCT” number:
NCT06517056
19.2  Defense Technical Information Center Registration (Optional):
Registration is not required 
Registration pending 
Registration complete 

20.0
 
References and Glossary
20.1  References:
Alami, S., Boutron, I., Desjeux, D., Hirschhorn, M., Meric, G., Rannou, F., & Poiraudeau, S. 
(2011). Patients“ and Practitioners” Views of Knee Osteoarthritis and Its Management: A 
Qualitative Interview Study. 
, (5), e19634. 
PLoS ONE 6
http://doi.org/10.1371/journal.pone.
0019634
Alison S. TB MED 592: Prevention and Control of Musculoskeletal Injury Associated with Physical 
Washington D.C.: Department of the Army; January 2006.
Training. 
Almeida SA, Williams KM, Shaffer RA, Brodine SK. Epidemiological patterns of musculoskeletal 
injuries and physical training. 
1999;31(8):1176-1182. 
Med Sci Sports Exerc. 
https://www.
ncbi.nlm.nih.gov/pubmed/10449021
Amoako, A. O., & Pujalte, G. G. A. (2014). Osteoarthritis in young, active, and athletic 
individuals. 
, , 27–32. 
Clinical Medicine Insights. Arthritis and Musculoskeletal Disorders 7
https://
www.ncbi.nlm.nih.gov/pmc/articles/PMC4039183/
Army Medical Surveillance Activity (AMSA). U.S. Army Center for Health Promotion and 
Preventive Medicine; 2005. 
. Accessed 
http://amasa.army.mil/AMSA/amsa_NS_home.htm
2005
Barton, C. J., Lack, S., Hemmings, S., Tufail, S., & Morrissey, D. (2015). The “Best Practice 
Guide to Conservative Management of Patellofemoral Pain”: incorporating level 1 evidence with 
expert clinical reasoning. 
, 
(14), 923–934. 
British Journal of Sports Medicine 49
https://bjsm.
bmj.com/content/49/14/923
Bedson, J., & Croft, P. R. (2008). The discordance between clinical and radiographic knee 
osteoarthritis: A systematic search and summary of the literature. BMC Musculoskeletal Disorders
, (1), 116. 
9
https://bmcmusculoskeletdisord.biomedcentral.com/articles/10.1186
/1471-2474-9-116
Bell DG, Jacobs I. Electro-mechanical response times and rate of force development in males and 
females. 
1986;18(1):31-36. 
Med Sci Sports Exerc. 
https://www.ncbi.nlm.nih.gov/pubmed
/3959861
Bensalma F, Hagemeister N, Cagnin A, Ouakrim Y, Bureau NJ, Choinière M, Mezghani N. 
Biomechanical markers associations with pain, symptoms, and disability compared to 
radiographic severity in knee osteoarthritis patients: a secondary analysis from a cluster 
randomized controlled trial. BMC Musculoskelet Disord. 2022 Oct 5;23(1):896. doi: 10.1186
/s12891-022-05845-1. PMID: 36199051; PMCID: PMC9533576. https://bmcmusculoskeletdis
ord.biomedcentral.com/articles/10.1186/s12891-022-05845-1
Boling, M. C., Padua, D. A., Marshall, S. W., Guskiewicz, K., Pyne, S., & Beutler, A. (2009). A 
prospective investigation of biomechanical risk factors for patellofemoral pain syndrome: the 
Joint Undertaking to Monitor and Prevent ACL Injury (JUMP-ACL) cohort. The American Journal of 
, 
(11), 2108–2116. 
Sports Medicine 37
htp://doi.org/10.1177/0363546509337934
Brunnekreef, J. J., van Uden, C. J., van Moorsel, S., & Kooloos, J. G. (2005). Reliability of 
videotaped observational gait analysis in patients with orthopedic impairments. BMC 
Musculoskeletal Disorders, 6(1), 2–9.
https://bmcmusculoskeletdisord.biomedcentral.com/articles/10.1186/1471-2474-6-
17
Cagnin, A., Choinière, M., Bureau, N. J., Durand, M., Mezghani, N., Gaudreault, N., & 
Hagemeister, N. (2019). A multi-arm cluster randomized clinical trial of the use of knee 
kinesiography in the management of osteoarthritis patients in a primary care setting. Postgraduat
, , 1–11. 
e Medicine 5
http://doi.org/10.1080/00325481.2019.1665457
Canham-Chervak M, Rappole C, Grier T, Jones BH. Injury Mechanisms, Activities, and Limited 
Work Days in US Army Infantry Units. US Army Med Dep J. 2018 Dec;(2–18):6–13. https://ww
w.ncbi.nlm.nih.gov/pubmed/30623393

Carender, C. N., Bollier, M. J., Wolf, B. R., Duchman, K. R., An, Q., & Westermann, R. W. (2019). 
Preoperative Performance of PROMIS in Patients With Patellofemoral Malalignment and Chondral 
Disease. Orthopaedic Journal of Sports Medicine, 7(7), 232596711985500–5. https://journals.
sagepub.com/doi/10.1177/2325967119855001
ClinicalTrials.gov. (n.d.). Trial of Self-managed Approaches for Patellofemoral Pain Syndrome in 
. Retrieved from 
Active Duty - Full Text View - ClinicalTrials.gov
https://clinicaltrials.gov/ct2
/show/study/NCT02597673
Crossley KM, Stefanik JJ, Selfe J, Collins NJ, Davis IS, Powers CM, McConnell J, Vicenzino B, 
Bazett-Jones DM, Esculier JF, Morrissey D, Callaghan MJ. 
, 2016 — 
Br. J. Sports Med.
Crossley, K. M., Macri, E. M., Cowan, S. M., Collins, N. J., & Roos, E. M. (2018). The 
patellofemoral pain and osteoarthritis subscale of the KOOS (KOOS-PF): development and 
validation using the COSMIN checklist. British Journal of Sports Medicine, 52(17), 1130–1136. htt
p://doi.org/10.1136/bjsports-2016-096776
de Oliveira Silva, D., Briani, R. V., Pazzinatto, M. F., Ferrari, D., Aragão, F. A., & de Azevedo, F. 
M. (2015). Reduced knee flexion is a possible cause of increased loading rates in individuals with 
patellofemoral pain. Clinical Biomechanics (Bristol, Avon), 30(9), 971–975. (https://www.ncbi.
)
nlm.nih.gov/pubmed/26169602
Dye S Patellofemoral pain current concepts: an overview. Sports Med Arthrosc Rev. 2001;9:264–
272. [
]
Google Scholar
Eastlack, M. E., Arvidson, J., Snyder-Mackler, L., Danoff, J. V., & McGarvey, C. L. (1991). 
Interrater Reliability of Videotaped Observational Gait-Analysis Assessments. Physical Therapy, 
71(6), 465 472. https://academic.oup.com/ptj/article-abstract/71/6/465/2728814
Evans, J., Smith, A., Gibbons, C., Alonso, J., & Valderas, J. (2018). The National Institutes of 
Health Patient-Reported Outcomes Measurement Information System (PROMIS): a view from the 
UK. Patient Related Outcome Measures, Volume 9, 345–352. http://doi.org/10.2147/PROM.
S141378
Fuentes, A., Pontbriand, R., Martin, N., & Therrien, M. (2013). Improved Management of Knee 
Osteoarthritis Using Dynamic Mechanical Assessment: A Case Series Report. Pmrj, 5(S), S232–
S233. http://doi.org/10.1016/j.pmrj.2013.08.368
Gaitonde, D. Y., ericksen, A., & Robbins, R. C. (2019). Patellofemoral Pain Syndrome. American 
, 
(2), 88–94. Retrieved from 
Family Physician 99
https://www.aafp.org/afp/2019/0115
/p88.html#afp20190115p088-b3
Hannan, M. T., Felson, D. T., & Pincus, T. (2000). Analysis of the discordance between 
radiographic changes and knee pain in osteoarthritis of the knee. 
, 
The Journal of Rheumatology 2
(6), 1513–1517. 
7
https://www.ncbi.nlm.nih.gov/pubmed/10852280
Hauret, K. G., Bedno, S., Loringer, K., Kao, T.-C., Mallon, T., & Jones, B. H. (2015). 
Epidemiology of Exercise- and Sports-Related Injuries in a Population of Young, Physically Active 
Adults. The American Journal of Sports Medicine, 43(11), 2645–2653. https://journals.
sagepub.com/doi/10.1177/0363546515601990
Jones BH, Knapik JJ. Physical training and exercise-related injuries. Surveillance, research and 
injury prevention in military populations. 
1999;27(2):111-125. 
Sports Med. 
https://www.ncbi.
nlm.nih.gov/pubmed/10091275
Jones BH, Perrotta DM, Canham-Chervak ML, Nee MA, Brundage JF. Injuries in the military: a 
review and commentary focused on prevention. 
2000;18(3 Suppl):71-84. 
Am J Prev Med. 
https:
//www.ncbi.nlm.nih.gov/pubmed/10736543
Jones BH, Hansen BC. An armed forces epidemiological board evaluation of injuries in the 
military. 
2000;18(3 Suppl):14-25. 
Am J Prev Med. 
https://www.ncbi.nlm.nih.gov/pubmed
/10736537
Jones BH, Hauschild VD. Physical Training, Fitness, and Injuries: Lessons Learned From Military 
Studies. J Strength Cond Res. 2015 Nov;29 Suppl 11:S57-64. doi: 10.1519/JSC.
0000000000001115. PMID: 26506200. https://journals.lww.com/nsca-jscr/fulltext/2015
/11001

 
Jones BH, Hauschild VD, Canham-Chervak M. Musculoskeletal training injury prevention in the U.
S. Army: Evolution of the science and the public health approach. J Sci Med Sport. 2018 Nov;21
(11):1139–46. https://www.ncbi.nlm.nih.gov/pubmed/29602720
Knapik JJ DS, Scott S, Hauret KG, Canada S, Marin R, Palkoska F, VanCamp S, Piskator E, Reiger 
W. Evaluation of two army fitness programs: The TRADOC standrized physical training program 
for basic combat training and the fitness assessment   program. 2004(12-HF-5772B-04):171.
Knapik, J. J., Jones, S. B., Darakjy, S., Hauret, K. G., Bullock, S. H., Sharp, M. A., & Jones, B. H. 
(2007). Injury rates and injury risk factors among U.S. Army wheel vehicle mechanics. Military 
Medicine, 172(9), 988–996. http://doi.org/10.7205/milmed.172.9.988
Kujala UM, Jaakkola LH, Koskinen SK, Taimela S, Hurme M, Nelimarkka O. Scoring of 
patellofemoral disorders. Arthroscopy. 1993;9(2):159-63. doi: 10.1016/s0749-8063(05)80366-
4. PMID: 8461073. https://www.sciencedirect.com/science/article/abs
Labbe, D. R., Hagemeister, N., Tremblay, M., & de Guise, J. (2008). Reliability of a method for 
analyzing three-dimensional knee kinematics during gait. Gait & Posture, 28(1), 170–174. http:/
/doi.org/10.1016/j.gaitpost.2007.11.002
Lincoln AE, Smith GS, Amoroso PJ, Bell NS. The natural history and risk factors of 
musculoskeletal conditions resulting in disability among US Army personnel. 
2002;18:99-
Work. 
113. https://www.ncbi.nlm.nih.gov/pubmed/12441574
Lustig, S., Magnussen, R. A., Cheze, L., & Neyret, P. (2012). The KneeKG system: a review of 
the literature. 
. 
Knee Surgery, Sports Traumatology, Arthroscopy : Official Journal of the ESSKA h
ttp://doi.org/10.1007/s00167-011-1867-4
Mauntel TC, Tenan MS, Freedman BA, Potter BK, Provencher MT, Tokish JM, Lee IE, Rhon DI, 
Bailey JR, Burns TC, Cameron KL, Grenier ES, Haley CA, Leclere LE, McDonald LS, Owens BD, 
Pallis MP, Posner MA, Rivera JC, Roach CJ, Robins RJ, Schmitz MR, Sheean AJ, Slabaugh MA, 
Volk WR, Dickens JF. The Military Orthopedics Tracking Injuries and Outcomes Network: A 
Solution for Improving Musculoskeletal Care in the Military Health System. Mil Med. 2022 Mar 28;
187(3-4):e282-e289. doi: 10.1093/milmed/usaa304. PMID: 33242087. https://academic.oup.
com/milmed/article/187/3-4/e282/6006710
Merican, A. M., & Amis, A. A. (2009). Iliotibial band tension affects patellofemoral and 
tibiofemoral kinematics, 
(10), 1539–1546. http://doi.org/10.1016/j.jbiomech.2009.03.041 
42
htt
ps://www.ncbi.nlm.nih.gov/pubmed/19481211
Mills, K., & Hunter, D. J. (2014). Best Practice & Research Clinical Rheumatology. Best Practice & 
, 
(1), 73–91. 
Research Clinical Rheumatology 28
http://doi.org/10.1016/j.berh.2014.01.006
Molloy JM, Pendergrass TL, Lee IE, Chervak MC, Hauret KG, Rhon DI. Musculoskeletal Injuries 
and United States Army Readiness Part I: Overview of Injuries and their Strategic Impact. Mil 
Med. 2020 Sep 18;185(9-10):e1461-e1471. doi: 10.1093/milmed/usaa027. PMID: 32175566. ht
tps://academic.oup.com/milmed/article/185/9-10/e1461/5805225
Mukaino, M., Ohtsuka, K., Tanikawa, H., Matsuda, F., Yamada, J., Itoh, N., & Saitoh, E. (2018). 
Clinical-oriented Three-dimensional Gait Analysis Method for Evaluating Gait Disorder. Journal of 
, (133), 1–7. 
Visualized Experiments
http://doi.org/10.3791/57063
Özdemir M, Kavak RP. Chondromalacia Patella among Military Recruits with Anterior Knee Pain: 
Prevalence and Association with Patellofemoral Malalignment. Indian J Orthop. 2019 Dec;53(6):
682–8.  https://www.ncbi.nlm.nih.gov/pubmed/31673166
Petersen, W., Ellermann, A., Gösele-Koppenburg, A., Best, R., Rembitzki, I. V., Brüggemann, G.-
P., & Liebau, C. (2013). Patellofemoral pain syndrome. Knee Surgery, Sports Traumatology, 
, 
(10), 2264–2274. 
Arthroscopy : Official Journal of the ESSKA 22
http://doi.org/10.1007
/s00167-013-2759-6
Powers, C. M., Heino, J. G., Rao, S., & Perry, J. (1999). The influence of patellofemoral pain on 
lower limb loading during gait. 
, 
(10), 722–728. 
Clinical Biomechanics (Bristol, Avon) 14
https://
www.ncbi.nlm.nih.gov/pubmed/10545627
Powers, C. (2003). The influence of altered lower-extremity kinematics on patellofemoral joint 
dysfunction: a theoretical perspective. 
, 
The Journal of Orthopaedic and Sports Physical Therapy 3
(11), 639. 
3
https://www.ncbi.nlm.nih.gov/pubmed/14669959

Rodriguez, M. J., Garcia, E. J., & Dickens, J. F. (2019). Primary and Posttraumatic Knee 
Osteoarthritis in the Military. 
, 
(2), 134–137. 
The Journal of Knee Surgery 32
http://doi.org/10.
1055/s-0038-1676956
Rudzki SJ. Injuries in Australian Army recruits. Part II: Location and cause of injuries seen in 
recruits. 
1997;162(7):477-480. 
Mil Med. 
https://www.ncbi.nlm.nih.gov/pubmed/9232977
Salsich, G. B., & Perman, W. H. (2007). Patellofemoral joint contact area is influenced by 
tibiofemoral rotation alignment in individuals who have patellofemoral pain. The Journal of 
, 
(9), 521–528. 
Orthopaedic and Sports Physical Therapy 37
https://www.ncbi.nlm.nih.gov
/pubmed/17939611
Sati, M., de Guise, J., Larouche, S., & Drouin, G. (1996). Quantitative assessment of skin-bone 
movement at the knee. The Knee, 3(3), 121–138. https://www.sciencedirect.com/science
/article/pii/0968016096002104
Simon, S. (2004). Quantification of human motion: gait analysis--benefits and limitations to its 
application to clinical problems, 
(12), 1869–1880. 
37
https://www.ncbi.nlm.nih.gov/pubmed
/15519595
Songer TJ, LaPorte RE. Disabilities due to injury in the military. 
2000;18(3 
Am J Prev Med. 
Suppl):33-40. https://www.ncbi.nlm.nih.gov/pubmed/10736539
Stathopulu, E., & Baildam, E. (2003). Anterior knee pain: a long-term follow-up. Rheumatology 
, 
(2), 380–382. 
(Oxford, England) 42
https://www.ncbi.nlm.nih.gov/pubmed/12595641
Teyhen DS, Goffar SL, Shaffer SW, Kiesel K, Butler RJ, Tedaldi A-M, et al. Incidence of 
Musculoskeletal Injury in US Army Unit Types: A Prospective Cohort Study. J Orthop Sports Phys 
Ther. 2018;48(10):749–57. https://www.ncbi.nlm.nih.gov/pubmed/29787695
Teyhen, D. S., Shaffer, S. W., Butler, R. J., Goffar, S. L., Kiesel, K. B., Rhon, D. I., et al. (2015). 
What Risk Factors Are Associated With Musculoskeletal Injury in US Army Rangers? A Prospective 
Prognostic Study. Clinical Orthopaedics and Related Research, 473(9), 2948–2958. http://doi.
org/10.1007/s11999-015-4342-6
Therrien, M., Fuentes, A., Landry, P., ElHachem, C., & Pontbriand, R. (2016). Real-world clinical 
result from a multimodal management program for knee osteoarthritis. Osteoarthritis and 
, 
(Supplement 1), S431. 
Cartilage / OARSI, Osteoarthritis Research Society 24
http://doi.org
/10.1016/j.joca.2016.01.779
Tiberio, D. (1987). The effect of excessive subtalar joint pronation on patellofemoral mechanics: 
a theoretical model. 
, (4), 160–165. 
The Journal of Orthopaedic and Sports Physical Therapy 9
htt
ps://www.ncbi.nlm.nih.gov/pubmed/18797010
U.S. Army Public Health Center internal analysis, Defense Medical Surveillance System database, 
completed 2018.
U.S. Army Medical Command internal analysis, Soldier Outcomes Trajectory Assessment (SOTA) 
database, completed July 2019.
U.S. Army Public Health Center internal analysis, Medical Operational Data System eProfile data, 
completed August 2019.
U.S. Army Medical Command internal analysis, Medical Operational Data System eProfile data, 
completed March 2019.
van der Worp MP, ten Haaf DSM, van Cingel R, de Wijer A, Nijhuis-van der Sanden MWG, Staal 
JB. Injuries in Runners; A Systematic Review on Risk Factors and Sex Differences. PLoS One 
[Internet]. 2015 Feb 23 [cited 2019 Nov 20];10(2). Available from: https://www.ncbi.nlm.
nih.gov/pmc/articles/PMC4338213/
van Gent RN, Siem D, van Middelkoop M, van Os AG, Bierma-Zeinstra SMA, Koes BW. Incidence 
and determinants of lower extremity running injuries in long distance runners: a systematic 
review. Br J Sports Med. 2007 Aug;41(8):469–80; discussion 480. https://www.ncbi.nlm.nih.
gov/pubmed/17473005

Waryasz, G. R., & Mcdermott, A. Y. (2008). Patellofemoral pain syndrome (PFPS): a systematic 
review of anatomy and potential risk factors. 
, (1), 9. 
Dynamic Medicine 7
http://doi.org/10.
1186/1476-5918-7-9
Willy, R. W., Hoglund, L. T., Barton, C. J., Bolgla, L. A., Scalzitti, D. A., Logerstedt, D. S., et al. 
(2019). Patellofemoral Pain. The Journal of Orthopaedic and Sports Physical Therapy, 49(9), 
CPG1–CPG95. https://www.jospt.org/doi/10.2519/jospt.2019.0302
Whitehead, A. L., Julious, S. A., Cooper, C. L., & Campbell, M. J. (2016). Estimating the sample 
size for a pilot randomised trial to minimise the overall trial sample size for the external pilot and 
main trial for a continuous outcome variable. 
, 
(3), 
Statistical Methods in Medical Research 25
1057–1073. http://doi.org/10.1177/0962280215588241
20.2  Abbreviations and Acronyms:
ADSM: Active Duty Service Member 
AKPS: Anterior Knee Pain Scale
GROC: Global Rating of Change
HCPs: Health Care Providers
MCAR: Missing Completely at Random
MTFs: Military Treatment Facilities
KneeKG: Knee Kinesiography
PF: Patellofemoral
PFP: Patellofemoral Pain
PFPS: Patellofemoral Pain Syndrome
PROMIS: Patient Reported Outcomes Measurement Information System
RTD: Return to Duty
UPIRTSO: unanticipated problems involving risk to subjects or others