Shared Decision Making Aid for Prosthetic Design
Conditions: Amputation, Prosthesis User
Sponsor: University of Colorado, Denver

Shared Decision Making Aid for Prosthetic Design
                                NCT04536025
                                   12.08.2020

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COMIRB Protocol 
COLORADO MULTIPLE INSTITUTIONAL REVIEW BOARD 
CAMPUS BOX F-490    TELEPHONE:  303-724-1055  Fax:  
303-724-0990 
 
 
 
Protocol #:  20-1070 
Project Title: Shared Decision Making Aid for Prosthetic Design 
 
 
Principal Investigator:  Cory Christiansen PT, PhD 
Version Date:  12.08.2020  
 
 
 
  
 
I. Hypotheses and Specific Aims:   
The overarching hypothesis of this work is that the lack of shared decision 
making (SDM) for prosthetic design and failure to match patient expectations with a 
prosthetic design plan result in poor health outcomes for patients with LLA. Shared 
decision making (SDM) is where clinicians and patients share the best available 
evidence for comparing options in order to achieve informed preferences for making 
health decisions.1 A patient’s involvement in their health care process is known to affect 
their satisfaction,2,3 adherence to care programs,4 and health outcomes.5 Clinical 
decision aids (DAs) support patients in SDM and making informed health decisions, by 
providing information on the available options and associated outcomes.6 DAs are 
intended to help patients clarify their values associated with the options and potential 
outcomes, to create a platform for communication with healthcare providers.6,7 DAs have 
been shown to improve patient knowledge and realistic expectations for given health 
options.1 This project aims to examine how to better align patient and clinician 
values and expectations by developing a DA for prosthetic design decision options, 
to support SDM between patients receiving their first prosthesis and prosthetic 
care providers. This proposal will be guided by the International Patient Decision Aids 
Standards (IPDAS).6-8 
Aim 1: Qualitatively define the key determinants and decisional needs of new prosthetic 
patients (n=14) and prosthetic care providers (n=20- 24) during prosthetic design, via semi 
structured interviews with patient participants and focus groups with prosthetist 
participants.  
Expected Result 1.1: Key determinants and decisional needs for prosthetic design will 
be defined using content analysis guided by the Ottawa Decision Support framework9 
for patients making health decisions, and the Model for Shared Decision Making in 
Clinical Practice.10  
Expected Result 1.2: Key stakeholders who contribute directly to prosthetic design 
decisions (e.g., patients with LLA, prosthetists, physicians, caregivers, close friends or 
family members) will be identified via purposive sampling, to inform the target end 
users of a DA prototype. 
Aim 2: Synthesize the evidence for prosthetic design decision options to develop a DA 
prototype. 
Expected Result 2.1: Via systematic literature review, a DA prototype will be 
developed from the evidence on prosthetic design decision options associated with 
decisional needs identified in Aim 1.  
Aim 3: Assess the DA prototype’s accuracy, comprehensibility, and usability through 
alpha testing with an expert working group of patients with LLA and prosthetic care 

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providers. 
Expected Result 3.1: Quantitative results from a Likert scale measurement of the DA 
prototype’s accuracy, comprehensibility and usability will inform revisions to the DA 
prior to use in a pilot clinical trial. 
Expected Result 3.2: Qualitative feedback on the DA prototype’s accuracy, 
comprehensibility, and usability will inform directed iterative revision for the DA 
prototype and implementation methods for use in a pilot clinical trial.  
 
II. Background and Significance:  
This proposal addresses three significant problems with conventional prosthetic 
design: 1) suboptimal patient outcomes after LLA; 2) challenges in the prosthetic design 
process that limit SDM; and 3) under-informed expectations for function with a prosthesis 
for patients and prosthetic care providers. 
2.1. High cost and suboptimal patient health and rehabilitation outcomes after LLA 
LLA is a high cost, chronic health condition marked by poor health-related 
outcomes.11-17 Five-year health care and prosthetic costs after amputation are estimated 
to be more than triple the lifetime health-care cost of an average person.16 In spite of the 
high cost and high resource allocation after LLA, strong evidence demonstrates a decline 
in functional outcomes, such as physical capacity (strength and balance), and walking 
ability (velocity and symmetry).18-20 Psychosocial outcomes (e.g., quality of life, 
depression) are also lower in people after LLA when compared to general population 
norms.11,12,17,21 When physical 
function and psychosocial 
outcomes are evaluated in 
combination, up to half of 
patients are unable to achieve 
their pre-amputation levels of 
mobility and quality of life one 
year after LLA.22,23 Thus, 
successful rehabilitation after 
LLA is multidimensional, 
involving many interrelated aspects of health outcomes.19,24 It is also unclear how health 
outcomes are affected by patient expectations and patient involvement in prosthetic 
design decisions.25,26 Shared Decision Making (SDM) is a process of supported patient 
and clinician communication to identify patient values and inform expectations about 
potential health options, and has been shown to improve patient satisfaction and 
adherence to care plans.1,4,26,27 SDM offers a solution for improving health-related 
outcomes after LLA through a mechanism of affective-cognitive (knowledge and 
understanding of options) and behavioral outcomes (adherence to care plans and 
adoption of health behaviors) (Figure 1).26 This proposal aims to improve the complex 
combination of both physical function and psychosocial outcomes of patients with LLA by 
supporting SDM in the prosthetic design process. 
2.2. Prosthetic design challenges that limit SDM 
One challenge in the prosthetic design process is the variety in patient characteristics 
that can be difficult to align with abundance of prosthetic design options available to 
choose from. Prosthetic deisgn options offer a range in technology, appearance, 

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functional performance, expense, maintenance, method of use, safety, and stability.28-30 
Components of the prosthetic design decision include selecting a prosthetic socket, 
interface, suspension system, components, and cover (Table 1). For example, prosthetic 
interfaces (e.g., gel, urethane, silicone) between the residual limb and the prosthetic 
socket may provide increased comfort and protection for bony prominences, however are 
also associated with increased cost, maintenance, and may be difficult to donn. 
Additionally, several patient-specific factors may influence prosthetic component selection 
(Table 2); for example, a patient with limited hand dexterity may benefit from a prosthetic 
suspension system that is easy to donn over a system that requires more upper extremity 
strength, such as a pin locking gel liner.  
However, gel liners may 
be more ideal for patients with 
high activity levels, due to the 
skin protecting features and 
reduced shear forces on the 
residual limb. Higher costing 
prosthetic design options tend 
to be associated with more 
advanced appearance, 
materials, technology, safety 
features, and greater user satisfaction, yet may be resisted by health-care financers, or be 
less than ideal in certain environments (maintenance, sweat management, access to 
electricity for charging, less resistant to water exposure).28 In order to optimize prosthetic 
design, prosthetic care providers are challenged with combining the best available 
evidence around prosthetic design options, their clinical expertise, patient-specific factors, 
and patient values.31-33 The most appropriate option for a given patient is often unclear, 
and matching the optimal prosthetic option to a patient’s need and potential remains 
difficult.28 The tradeoffs in the prosthetic design decision making process emphasize the 
need for decision support for both patients and prosthetic care providers.28,34 
Challenges in the prosthetic design process contribute to a lack of SDM between 
patients with LLA and their healthcare providers. In the general population, most patients 
prefer to be active partners in decisions about their healthcare.26,35 Effective SDM 
between patients and health care providers is associated with greater patient satisfaction 
with care processes, adherence to treatment programs, improved self-reported health, 
and overall informed expectations.1-4,26 However, patients with LLA assume passive roles 
in the prosthetic design process due to a lack of knowledge and experience necessary to 
collaborate in prosthetic decisions.36 Discussing options and recognizing patient 
preferences is acknowledged as an important factor in improving prosthetic use and 
adherence to care plans, even when options are limited.37 The proposed project aims to 
improve the exchange of information about prosthetic design options between patients 
and their prosthetic care providers, in order to align values with prosthetic design 
decisions.  
2.3. Under-informed patient and prosthetic care provider expectations 
Both patient and prosthetic care provider expectations around anticipated function with 
a prosthesis are under-informed.36,38,39 Patients with LLA do not know what to expect from 
their first prosthesis, and their expectations for returning to pre-amputation levels of 
Key Decision: Prosthetic Design 
Decision Components 
Potential Decision Options 
Prosthetic Socket 
Total surface bearing, patellar tendon 
bearing, ischial containment, 
quadrilateral socket 
Prosthetic Interface 
Sock, gel, silicone, urethane, foam  
Prosthetic Suspension 
Suction, pin, lanyard, sleeve, belt 
Prosthetic Components  
Prosthetic foot, knee 
Prosthetic Cover 
Foam, protective skin, no cover 
Table 1. Potential Prosthetic Design Subcomponents & Decision Options 

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function after LLA are often unrealistically high.38,39 The tendency for patients to believe 
that parts of a prosthesis determine their ability to walk rather than their own physical 
ability is a prevalent concern among prosthetic care providers.39 Prosthetic care providers 
also express difficulty predicting patient health outcomes with a prosthesis, further 
contributing to the ambuiguity of both patient and clincian expectations for prosthetic 
rehabilitation.39 The lack of informed expectations may potentially link to reported low 
levels of patient satisfaction for function with a prosthesis,40,41 and prosthetic non-use 
rates by patients as high as 15%.42 Thus, managing unrealistic patient expectations in the 
prosthetic design process is a difficult endeavour and often viewed negatively in prosthetic 
care.39 In other populations, patient expectations for a given outcome are associated with 
success in rehabilitation, adherence to care plans, and improved functional recovery.5,43-45 
In a review on patient expectations after a surgical intervention, patients whose functional 
expectations were fulfilled had higher gains in satisfaction and physical quality of life.45-47 
In contrast, patients with unrealistic expectations for a given outcome after a health event 
may become discouraged and fail to meet their maximum potential.48 In order to achieve 
patient satisfaction with prosthetic care, a patient’s expectations for a prosthesis must 
align with their experience.41 We hypothesize that the failure to match patient expectations 
with a prosthetic design plan result in poor health-related outcomes for patients with LLA. 
The proposed project aims to inform realistic patient expectations during the prosthetic 
design process, to improve health-related outcomes after LLA. 
 
III. Preliminary Studies/Progress Report:   
Existing research has identified that DA address problems in conventional healthcare 
by: 1) improving patient health outcomes by providing high quality information on the 
available prosthetic design options and associated outcomes; 2) supporting patients and 
care providers in identifying and discussing values associated with healthcare options and 
reducing decisional conflict; and 3) aligning patient and care provider goals and values to 
inform expectations for healthcare options.  
3.1. Decision Quality: DA to improve LLA health outcomes 
The relationship between patient health outcomes after LLA and SDM has yet to be 
explored.26 A potential mechanism for improving health-related outcomes after LLA is 
through SDM by means of improving patient knowledge and understanding of prosthetic 
design options.26 DAs are designed to support patients and healthcare providers in SDM 
by providing high quality information on available decision options,6 and have been shown 
to improve patient knowledge of options by as much as 20%.1,49,50 Through the 
development and use of an innovative DA for prosthetic design, patients with LLA will gain 
new access to knowledge (high quality evidence) necessary to participate in decision 
making for their prosthesis. Upon completion, this proposal will be positioned to examine 
patient knowledge of prosthetic design options in concordance with patient health 
outcomes.  
3.2. Quality of Decision Making: Increase SDM and reduce decisional conflict in prosthetic 
design 
The proposed study will introduce SDM to the prosthetic design process using a novel 
DA to promote discussion of prosthetic design options, thus reducing decisional conflict. 
SDM has been shown to help patients make informed decisions that are in line with their 

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goals and values,51,52 and can be valuable for situations where evidence is insufficient or 
when personal preferences heavily influence the decision.53 Furthermore, the use of DAs 
has been shown to increase the likelihood of discussing potential decisions, patient 
participation, and decrease decisional conflict by up to 10%.1,50 Given the problem of 
limited patient participation in prosthetic design decisions, this proposal offers a solution 
for improving the quality of decision making in the prosthetic design process by supporting 
SDM between prosthetic care providers and patients. This proposal will also explore 
methods for implementing the use of a DA and identify areas for training on SDM in the 
prosthetic design process. 
3.3. Decision Quality: Align patient and prosthetic care provider values to inform 
expectations 
The proposed study will create and test a DA that improves values-treatment 
concordance for prosthetic design decisions in order to create realistic expectations for 
selected prosthetic options. This is important, as it will translate directly to clinical practice 
by helping patients construct and communicate personal values associated with the 
different options. A crucial aspect of the proposed study is the solution for uninformed 
patient and prosthetist expectations by means of a DA, to create a platform for aligning 
both patient and provider values (the benefits or risks that matter most) around the 
potential options, thus creating more realistic expectations for the outcome of each 
option.54 DAs have been shown to improve the congruency between the decision and 
patients’ values by as much as 51%, and improve realistic expectations of option 
outcomes by as much as 82%.1,50 The proposed study will create a DA that is a new and 
innovative approach to improving values-treatment concordance for prosthetic design 
decisions, in order to create realistic expectations for selected prosthetic options.  
 
IV. Research Methods 
 
A. Outcome Measure(s):   
A.1. Aim 1: Qualitative Scoping Outcome Measures 
Semi-structured interviews with participants with LLA will be conducted by a 
trained qualitative interviewer using video web conferencing with audio recording. Video 
conferencing will provide the benefits of in-person interviews (e.g., developing rapport, 
increasing accuracy, adding validity) while reducing participant travel burden.55 One-on-
one semi-structured interviews with participants with LLA provide the opportunity for the 
interviewer/interviewee to diverge and pursue an idea or response in more detail (i.e., 
discussion of personal values associated with prosthesis design).56,57  Therefore, one-on-
one semi-structured interviews provide the greatest potential for collecting high-quality 
data contributing to the decisional needs of prosthesis users.  Interview guides will be 
informed by peer reviewed literature on prosthetic design, the Shared Decision Making 
Model for Clinical Practice,10 and the Ottawa Decision Support Framework9 and contain 
broad, open-ended questions to explore perspectives on prosthetic decision making. 
Focus groups are advantageous when the best information is likely to come from 
group interaction,58 and will be conducted with prosthetist participants by a trained 
qualitative interviewer using video web conferencing with audio recording.  Given the 
professional nature of the decision and environment in which prosthetic design decisions 
take place, the collaborative group approach within a focus groups will likely provide 

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optimal high quality, rich data around the decisional needs of prosthetists. 
In addition to qualitative data collection, descriptive data will be collected from all 
recruited participants (prosthetists and patients with LLA), including demographics, the 
Control Preferences Scale59 (a measurement of preferences regarding participation in 
healthcare decisions), and the eHealth Literacy Scale60 (a measurement of perceived 
ability to find and use traditional, scientific, media, and computer health information), in 
order to inform future methods for implementation of the DA. 
A.2. Aim 2: Systematic Review and Synthesis of the Evidence Outcome Measures 
The quality of the studies will be evaluated using the Cochrane Criteria List for 
Methodological Quality Assessment.61 Finally, evidence will be summarized and 
interpreted, to guide the development of the DA. Results will be reviewed via focus groups 
by the expert working group, to confirm accuracy and credibility.6  
A.3. Aim 3: Alpha Testing with the Expert Working Group Outcome Measures 
The DA will be presented to the expert working group, and feedback on the 
accuracy, comprehensibility, and usability of the DA prototype will be collected. This study 
will use descriptive statistics for evaluating accuracy, comprehensibility, and usability of 
the DA. Accuracy of the DA will be determined by the percentage of expert working 
group members who perceive the presented risks and benefits in the DA to align with the 
scientific evidence available on the prosthetic design decision outcomes.50 
Comprehensibility of the DA will be classified as the degree to which the DA content 
covers information necessary for making an informed decision about prosthetic design, 
and will be evaluated using a Likert scale for each component of the DA.6,62,63 Usability 
will be qualified as the extent to which the information presented in the DA is clear, 
understandable, and effective, and will be evaluated using a Likert scale for each 
component of the DA.63 Additional feedback on the accuracy, comprehensibility, and 
usability of the DA prototype will be collected by means of short individual semi-structured 
interviews after each round of alpha testing.  
 
B. Description of Population to be Enrolled:   
B.1. Aim 1-3:  Assemble an expert working group 
A separate expert working group will be assembled for consultation throughout 
all aims of the proposed work, and for alpha testing in Aim 3. In order to check the 
credibility of results and ensure all appropriate topics necessary for prosthetic design 
decision making are included in an initial DA prototype, focus groups will be conducted 
with the expert working group to review and confirm the results from Aims 1 and 2. In 
order to alpha test the DA prototype in Aim 3, quantitative data and semi-structured 
individual interviews will be conducted with the expert working group. 
The expert working group will consist of at least 5 and up to 12 people with LLA 
actively receiving prosthetic care, and at least 5 and up to 12 prosthetic care providers 
with greater than 5 years of experience. Individuals will be invited to join the expert 
working group based on expertise, and representation of key stakeholders relevant to 
the prosthetic design process identified in Aim 1 (e.g., certified prosthetists, therapists, 
physicians, and other caregivers).64 Patient expert group members will be identified 
through the University of Colorado Health Amputee Support Group, through the Amputee 
Coalition of America, and through Amputee List Serve (AMP-L). Healthcare provider 
expert group members will be identified through local and professional clinic partners and 
the Orthotics and Prosthetics List Serve. The group will be referred to for checking 
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of the DA. 
 
B.2. Aim 1: Qualitative Study Participants and Sampling Plan 
Participants (estimated up to 14 patients, within 1 year from lower limb amputation, 
receiving their first prosthesis and up to 24 prosthetic care providers) will be recruited 
through well-established clinical partners representing diverse prosthetic practice 
environments (including the Denver VA Medical Center and private prosthetics practices), 
located in Albuquerque, NM, Tucson, AZ, and Denver, CO, and clinics throughout the US. 
Patient participants will also be recruited through the Amputee Coalition of America, and 
through Amputee List Serve (AMP-L).  Standard to qualitative research methods, 
purposive sampling will be employed to ensure maximum variation of socio-demographic 
and clinical characteristics, and to ensure inclusion of all key stakeholders in the 
prosthetic design process.65 Prosthetic care providers will be sampled based on a diverse 
representation of professional experience and involvement in the prosthetic design 
process, including prosthetists, therapists, physicians, and associated care providers. 
Patient participants will be sampled based on diverse representation of above- and below-
knee amputation, age, sex, etiology, and availability to participate in a 1-hour, semi-
structured interview. The patient sample is expected to reflect a distribution of amputation 
levels and etiologies similar to population-level estimates: ~54% vascular and ~45% 
traumatic etiology.66 Patients will be recruited early in their rehabilitation process, for 
insight into the decisional needs for their first prosthesis and initial care planning. 
Recruitment will target 14 patients and 24 prosthetic care providers with the goal of 
achieving thematic saturation, the point where no additional properties of themes emerge 
from qualitative analysis.67-69 If thematic saturation has not been attained, enrollment will 
continue beyond the targets for each group. 
 
C. Study Design and Research Methods   
C.1. Overview of Approach 
The goal of this proposal is to develop and conduct alpha testing of a DA for prosthetic 
design decisions. The aims in this proposal are guided by IPDAS for developing patient 
decision aids (Figure 2).63  
Figure 2: Steps for development of a DA, adapted from the International Patient Decision Aids guidelines, Coulter et al.63 
Steps will include Aim 1) qualitatively define the scope and purpose of the DA; Aim 2) 
review and synthesize the available evidence to inform the development of a prosthetic 
design DA prototype; and Aim 3) alpha testing for accuracy, comprehensibility, and 
usability of the DA, with an expert group of patients and prosthetic care providers. Aims 1 
and 2 are an exploratory sequential mixed methods study design for developing the DA, a 
commonly used study design for instrument development.70 Aim 3 is a convergent parallel 
mixed method design for alpha testing of the DA. (Figure 3) 

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Figure 3: Study design overview 
C.2. Aim 1: Define the Scope and Purpose of the DA 
The objective of Aim 1 is to qualitatively define the scope and purpose of the DA, by 
exploring the key determinants for prosthetic design decisions, and decisional needs of 
both patients and prosthetic care providers during prosthetic design.63,71 This aim will 
clarify 1) all components of prosthetic design decisions that will be included in the DA 
prototype, 2) the key determinants that contribute to decision making, 3) the target end 
users of the DA, and 4) the necessary content to be included in the DA that will help 
inform the decision. 
C.3. Aim 2: Review the Evidence for Prosthetic Design Decision Options to Develop a DA 
Prototype. 
The purpose of Aim 2 will be to develop a DA prototype for new prosthetic users over 
two steps: 1) systematic review of the evidence on the prosthetic design decision options 
identified in Aim 1 and their associated risks and benefits; and 2) development of a DA 
prototype.63,71 
C.3.1. Aim 2: Systematic Review and Synthesis of the Evidence on Prosthetic Design 
Decision Options 
A comprehensive systematic literature review will be conducted on the relevant data 
and evidence associated with the available options, as they relate to the key components 
of prosthetic design decisions and the decisional needs defined in Aim 1.63 The review will 
appraise the available evidence on the risks and benefits of the possible choices 
associated with each component of prosthetic design, and summarize the results in a final 
document.63 The systematic review will follow the Cochrane Handbook and PRISMA 
Guidelines for Systematic Reviews.61,72  
C.3.2. Aim 2: Developing a DA Prototype 
The development of the DA proposed in this study will follow the IPDAS guidelines for 
decision aid development.6,8 Based on this guideline, the DA will include high quality 
evidence on the options in sufficient detail for each decision associated with prosthetic 
design, potential outcome probabilities, clarity for identifying patient values associated 
with each option, and guidance on deliberation and communication.8 Use of plain 
language will be implemented and checked by the expert working group, for 
comprehensiveness for all literacy levels.8 Format of the decision aid will be established 
(i.e., paper article, video, web-based).63,71 For accessibility in multiple environments (long 
distance vs. local, internet access vs. no technology access), a minimum of two formats 
will be considered.71 
C.4. Aim 3: Assess the Accuracy, Comprehensibility, and Usability of the DA Through 
Alpha Testing with the Expert Working Group of Patients and Associated Healthcare 
Providers. 
The objective of this aim is to assess the accuracy, comprehensibility, and usability of 

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the DA through alpha testing with an expert working group established in Aim 1. The DA 
will be presented to the expert working group, and feedback on the accuracy, 
comprehensibility, and usability of the DA prototype will be collected. Evaluating the 
accuracy, comprehensibility, and usability of the DA with potential end-users will ensure 
that 1) the DA contains high quality accurate information, 2) the DA presents material that 
is valuable to the decision making process for prosthetic design, and 3) the DA is logical 
and understandable to the target end users, and can be feasibly and rapidly adopted in 
practice.1,63,70,73 Both qualitative and quantitative data will be collected and analyzed 
separately, to create a more complete understanding of the DA’s accuracy, 
comprehensibility, and usability.70 The alpha testing will inform iterative modifications to 
the DA in future prototypes, and will produce findings that will determine whether the DA 
should be recommended for pilot testing in the clinic setting.74  
 
  
D. Description, Risks and Justification of Procedures and Data Collection 
Tools: 
 
The risks associated with the semi-structured interviews are minimal. Additionally, the 
quantitative measures to be used (e.g., questionnaires) are low-risk and considered to be 
safe. These minimal and low-risks include the risk of misinterpretation of discussion and 
questionnaires, potentially resulting in negative or unproductive thoughts by the patient or 
prosthetist. Additionally, one purpose of the semi-structured interviews is to uncover any 
unforeseen consequences of the information included in DA (e.g., patient anxiety about 
prosthetic decisions, recovery) and to address these risks. It is also important to note that 
patients and therapists already discuss prosthetics and prognosis as part of standard 
care, however currently these discussions are woefully under-informed by evidence.  
Finally, rare, unknown, or unforeseeable (unexpected) risks may also occur. 
 
As with all clinical research studies, there is the general risk of breach of confidentiality 
or data security. To minimize this risk, only the minimal necessary data will be collected, 
and procedures to maintain confidentiality will be followed. 
Little research has been conducted to promote shared decision making as a method 
for improving patient outcomes for people with LLA. This study will initiate work on 
developing a DA prototype to identify the potential for efficacy and implementation in 
clinical practice. The patient and clinician participants have potential to benefit 
immediately from the educational experience surrounding interaction with research team 
who are highly interested in addressing functional limitations and disability following non-
traumatic lower-limb amputation. In addition, the results of the study will indicate whether 
larger efforts (i.e., Phase II trial) are indicated to test implementation of such intervention 
as a key element of standard prosthetic design decisions following LLA.  
    
E.   Potential Scientific Problems:   
Due to the pilot design of the proposed study, and to maximize successful use of DA, 
we have selected optimal champion clinic partners for our initial Aim 1 qualitative 
exploration and for the expert working group. Participant selection will be, in part, based 
on their willingness participate in feedback on incorporating novel measures into practice, 
which may introduce limitations in generalizability and bias around future DA 
implementation in other clinics. Therefore, data collection and recruited participants will be 
a convenience sample, which may introduce limitations in generalizability and bias around 
future DA testing in other clinics. 
 
F.   Data Analysis Plan:   

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F.1. Aim 1: Qualitative Data Analysis 
Transcripts from the semi-structured interviews and focus groups will be analyzed with 
ATLAS.ti 7.0 software using qualitative directed content analysis.75,76 Qualitative directed 
content analysis is a process where existing theory guides the discussion and 
interpretation of the research findings, providing focus for the research question, to 
produce a final identification of themes, patterns, or categories.75 Pre-determined codes 
will be based on steps of SDM defined by the Shared Decision Making Model for Clinical 
Practice,10 and on existing theory of decisional needs, as described by the Ottawa 
Decision Support Framework.9 In order to maintain inter-coder reliability, two members of 
the research team (one clinician and one non-clinician, to manage potential biases) will 
independently review and code the transcripts, and reconcile results. Codes will be 
modified or added as needed; any new material that does not fit with existing codes will be 
discussed to further extend or refine the existing decisional needs.75 In the circumstance 
of any disagreements, a third team member will consult. Codes will then be grouped into 
themes to identify the primary components of prosthetic design decisions, determine the 
key determinants for each decision, and identify the decisional needs of both patients and 
prosthetic care providers. To maintain unbiased results and trustworthiness of the 
findings, coding rules and an audit process will be used.76 Credibility of results will be 
ensured by conducting focus groups to share and evaluate the final themes with an 
established expert working group of prosthetic care providers and patients with LLA 
(described below). In order to develop a DA prototype in Aim 2, this aim will clarify the 
primary decisions and identify the key decisional needs (e.g., knowledge needs of patients 
and healthcare providers, associated values). Results from this aim will be foundational 
for defining current SDM practices in prosthetic design, identifying areas of need for 
decision support, identifying end users of the DA, and informing a SDM training and 
implementation strategy in future pilot work. 
F.2. Aim 2: Systematic Review Analysis 
The systematic review will follow the Cochrane Handbook and PRISMA Guidelines for 
Systematic Reviews.61,72 Two study reviewers will identify relevant work from multiple 
resources (e.g., MEDLINE, EMBASE). Key search terms and inclusion criteria will be 
established prior to searching for identifying relevant work (e.g., pertaining to LLA 
participants, inclusion of outcomes of interest, key words reflective of the decisional needs 
identified in Aim 1). The quality of the studies will be evaluated using the Cochrane 
Criteria List for Methodological Quality Assessment.61 Finally, evidence will be 
summarized and interpreted, to guide the development of the DA. Results will be reviewed 
via focus groups by the expert working group, to confirm accuracy and credibility.6  
F.3. Aim 3: Alpha Testing and Iterative Modification With the Expert Working Group 
The DA will be presented to the expert working group, and feedback on the 
accuracy, comprehensibility, and usability of the DA prototype will be collected. All 
quantitative data will be collected through Research Electronic Data Capture (REDCap) 
and analyzed with R, version 3.5.1. This study will use descriptive statistics for evaluating 
accuracy, comprehensibility, and usability of the DA. Based on thresholds in published 
testing of accuracy, comprehensibility, and usability of existing DAs, 80% will be the 
threshold for each component of the prosthetic design decision included in the DA. If 
accuracy, comprehensibility, and usability score less than 80%, the DA will be revised and 
an additional round of alpha testing will be conducted. Iterative revisions to the DA and 
rounds of alpha testing will continue until all outcomes measure 80% or greater. 
 Additional feedback on the accuracy, comprehensibility, and usability of the DA 

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prototype will be collected by means of short individual semi-structured interviews after 
each round of alpha testing. Results from the qualitative feedback on the DA prototype will 
inform revisions to the prototype for additional rounds of alpha testing, and inform an 
implementation plan for future clinical use of the DA, including training on SDM in 
prosthetic care. Thematic analysis will be used to analyze results from the Aim 3 
qualitative interviews.65 An initial coding team of 3 researchers will develop the code book 
for each group of interviews (patients and prosthetic care providers), and once agreement 
is established (estimated 3-6 interviews), remaining transcripts will be coded by two 
primary coders. The coding team will include both clinical and non-clinical members to 
minimize potential bias (e.g., prosthetist, occupational therapist, and non-clinical research 
assistant). All transcripts will be coded and analyzed via open coding using Atlas.ti 
software. Methods for maintaining trustworthiness and credibility will reflect those listed in 
Aim 1.  
Finally, in the convergent mixed methods design, qualitative and quantitative data 
from Aim 3 will be individually analyzed and then consolidated to explain any unanswered 
questions or unexpected findings in the alpha testing of the DA. Common concepts will be 
integrated and compared to identify and describe feasibility and acceptability results, 
using data consolidation and merging.70 Data connection methods will be used to 
maximize strengths and minimize weaknesses of both qualitative and quantitative 
results.70 Results from the analysis will further improve and tailor the DA to fit the need of 
both patients and prosthetic care providers, and inform study procedures and 
implementation methods for pilot testing in a clinical beta testing trial. Modifications will be 
made to the DA in an iterative process (at least two rounds of testing and modification with 
the expert working group, or until greater than 80% DA accuracy, comprehensibility, and 
usability is achieved) to ensure that the DA is optimal for clinical implementation.6 An audit 
trail will be maintained through the modification process, for reporting feedback and how 
this feedback was incorporated into the design.8 
 
 
G.  Summarize Knowledge to be Gained:   
This study focuses on a prevalent and understudied population of people with LLA. 
Due to high heterogeneity and limited evidence on what factors are important in prosthetic 
design decisions, the outcomes following LLA are poor. With little to no additional risk, this 
exploratory sequential trial has high potential to develop a method intended to improve 
SDM for prosthetic design and to advance the quality and reduce the overall health 
consequences (and costs) for patients with LLA.  
An abundance of prosthetic design options are available, ranging in appearance, 
functional performance, expense, maintenance, and method of use.28,30 However, 
matching prosthetic design options with a patient’s values, expectations, and functional 
potential remains a challenge, and this can affect patient outcomes.28,34 For example, 
patients with LLA report having expectations for returning to normal after receiving their 
prosthesis,38 yet up to 50% are unable to achieve ambulation necessary for activities of 
daily living one year after amputation,23,77 and patient satisfaction with their prosthetic care 
remains low.40,41 These outcomes suggest that prosthetic design decisions may not align 
with patient values or expectations for function, highlighting the need to incorporate 
patient preferences in the prosthetic design process.37  

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Currently, clinician and patient expectations for function with a prosthesis are 
underinformed.28,39 Prosthetic care providers report difficulty estimating patient outcomes 
after LLA, managing patient expectations, and interpreting existing evidence around 
prosthetic design options, and instead rely on past experiences for subjective prosthetic 
design decisions.28,39 Thus, up to 30% of patients may be using prosthetic components 
designated for a functional level lower than their current functional capacity.78 Additionally, 
providing rationale for prosthetic design decisions remains challenging for prosthetic care 
providers,28 limiting shared patient-provider involvement in weighing outcomes associated 
with the potential prosthetic options. On the other hand, patients report unmet 
expectations between their goals and the capabilities of a prosthesis,36,38 and general 
uncertainty throughout the rehabilitation process.38 Although patients express a desire to 
be more involved in the prosthetic design process, their involvement in prosthetic decision 
making is minimal.36-38 Patient involvement in prosthetic design decision making and their 
expectations of function with a prosthesis may have an important influence on functional 
recovery, however this relationship remains unclear.25,26  
The development of a novel DA for prosthetic design will address the challenge of 
matching patient expectations with prosthetic design. The DA is an innovative tool 
designed to support patients and healthcare providers in SDM and making informed 
health decisions, by providing information on the available options and associated 
outcomes.6 DAs are intended to help patients clarify their values associated with the 
options and potential outcomes, to create a platform for communication with healthcare 
providers.6,7 DAs have been shown to improve patient knowledge and realistic 
expectations for given health options.1 This proposed study will be guided by the 
International Patient Decision Aids Standards (IPDAS)63 to develop a DA to enable shared 
decision making and translation of evidence to the point of care. 
Two key deliverables of this proposed study will be a final DA prototype for beta 
testing in a clinical pilot trial to examine efficacy and implementation of the DA for 
prosthetic design, and an implementation plan for rolling out the DA in clinical practice. 
The future clinical trial will be planned in the final quarter of the proposed study period.  
 
 H. References: 
 
1. 
Elwyn G, Edwards A, Thompson R. Shared decision-making in health care : achieving 
evidence-based patient choice. In: Third edition. ed. Oxford, United Kingdom ; New York, 
NY, United States of America: Oxford University Press,; 2016. 
2. 
Loh A, Simon D, Wills CE, Kriston L, Niebling W, Harter M. The effects of a shared 
decision-making intervention in primary care of depression: a cluster-randomized 
controlled trial. Patient Educ Couns. 2007;67(3):324-332. 
3. 
Bertakis KD. The communication of information from physician to patient: a method for 
increasing patient retention and satisfaction. J Fam Pract. 1977;5(2):217-222. 
4. 
Roter DL, Hall JA, Merisca R, Nordstrom B, Cretin D, Svarstad B. Effectiveness of 
interventions to improve patient compliance: a meta-analysis. Med Care. 1998;36(8):1138-
1161. 
5. 
Mondloch MV, Cole DC, Frank JW. Does how you do depend on how you think you'll do? 
A systemic review of the evidence for a relation between patients' recovery expectations 
and health outcomes (vol 165, 174, 2001). Can Med Assoc J. 2001;165(10):1303-1303. 
6. 
Elwyn G, O'Connor A, Stacey D, et al. Developing a quality criteria framework for patient 
decision aids: online international Delphi consensus process. BMJ. 2006;333(7565):417. 

Protocol Template 
Page 13 
CF-146, Effective 7/10/11 
 
7. 
Volk RJ, Llewellyn-Thomas H, Stacey D, Elwyn G. Ten years of the International Patient 
Decision Aid Standards Collaboration: evolution of the core dimensions for assessing the 
quality of patient decision aids. BMC Med Inform Decis Mak. 2013;13 Suppl 2:S1. 
8. 
Elwyn G, O'Connor AM, Bennett C, et al. Assessing the quality of decision support 
technologies using the International Patient Decision Aid Standards instrument (IPDASi). 
PLoS One. 2009;4(3):e4705. 
9. 
O'Connor AM, Drake ER, Fiset V, Graham ID, Laupacis A, Tugwell P. The Ottawa patient 
decision aids. Eff Clin Pract. 1999;2(4):163-170. 
10. 
Elwyn G, Frosch D, Thomson R, et al. Shared decision making: a model for clinical 
practice. J Gen Intern Med. 2012;27(10):1361-1367. 
11. 
Coffey L, Gallagher P, Horgan O, Desmond D, MacLachlan M. Psychosocial adjustment to 
diabetes-related lower limb amputation. Diabet Med. 2009;26(10):1063-1067. 
12. 
Horgan O, MacLachlan M. Psychosocial adjustment to lower-limb amputation: a review. 
Disabil Rehabil. 2004;26(14-15):837-850. 
13. 
Kahle JT, Highsmith MJ, Schaepper H, Johannesson A, Orendurff MS, Kaufman K. 
Predicting Walking Ability Following Lower Limb Amputation: An Updated Systematic 
Literature Review. Technol Innov. 2016;18(2-3):125-137. 
14. 
Kate Sansam M, Vera Neumann, MD, FRCP, Rory O'Connor, MD, MRCP and Bipin 
Bhakta MD, FRCP. Predicting Walking Ability Following Lower Limb Amputation:  A 
Systematic Review of the Literature. J Rehabil Med. 2009;41:593-603. 
15. 
Christiansen CL, Fields T, Lev G, Stephenson RO, Stevens-Lapsley JE. Functional 
Outcomes After the Prosthetic Training Phase of Rehabilitation After Dysvascular Lower 
Extremity Amputation. Pm&R. 2015;7(11):1118-1126. 
16. 
Sheehan TP, Gondo GC. Impact of limb loss in the United States. Phys Med Rehabil Clin 
N Am. 2014;25(1):9-28. 
17. 
Madsen UR, Baath C, Berthelsen CB, Hommel A. Age and health-related quality of life, 
general self-efficacy, and functional level 12 months following dysvascular major lower limb 
amputation: a prospective longitudinal study. Disabil Rehabil. 2018:1-10. 
18. 
Renstrom P, Grimby G, Larsson E. Thigh muscle strength in below-knee amputees. Scand 
J Rehabil Med Suppl. 1983;9:163-173. 
19. 
van Velzen JM, van Bennekom CA, Polomski W, Slootman JR, van der Woude LH, 
Houdijk H. Physical capacity and walking ability after lower limb amputation: a systematic 
review. Clin Rehabil. 2006;20(11):999-1016. 
20. 
Isakov E, Burger H, Gregori, et al. Isokinetic and isometric strength of the thigh muscles in 
below-knee amputees. Clin Biomech (Bristol, Avon). 1996;11(4):232-235. 
21. 
Sinha R, van den Heuvel WJ, Arokiasamy P. Factors affecting quality of life in lower limb 
amputees. Prosthet Orthot Int. 2011;35(1):90-96. 
22. 
Norvell DC, Turner AP, Williams RM, Hakimi KN, Czerniecki JM. Defining successful 
mobility after lower extremity amputation for complications of peripheral vascular disease 
and diabetes. J Vasc Surg. 2011;54(2):412-419. 
23. 
Schoppen T, Boonstra A, Groothoff JW, de Vries J, Goeken LN, Eisma WH. Physical, 
mental, and social predictors of functional outcome in unilateral lower-limb amputees. Arch 
Phys Med Rehabil. 2003;84(6):803-811. 
24. 
Schaffalitzky E, Gallagher P, MacLachlan M, Wegener ST. Developing consensus on 
important factors associated with lower limb prosthetic prescription and use. Disabil 
Rehabil. 2012;34(24):2085-2094. 
25. 
Balk EM, Gazula A, Markozannes G, et al. In: Lower Limb Prostheses: Measurement 
Instruments, Comparison of Component Effects by Subgroups, and Long-Term Outcomes. 
Rockville (MD)2018. 
26. 
Shay LA, Lafata JE. Where is the evidence? A systematic review of shared decision 
making and patient outcomes. Med Decis Making. 2015;35(1):114-131. 
27. 
Elwyn G, Laitner S, Coulter A, Walker E, Watson P, Thomson R. Implementing shared 
decision making in the NHS. BMJ. 2010;341:c5146. 

Protocol Template 
Page 14 
CF-146, Effective 7/10/11 
 
28. 
van Twillert S, Geertzen J, Hemminga T, Postema K, Lettinga A. Reconsidering evidence-
based practice in prosthetic rehabilitation: a shared enterprise. Prosthet Orthot Int. 
2013;37(3):203-211. 
29. 
Kahle JT, Highsmith MJ, Hubbard SL. Comparison of nonmicroprocessor knee mechanism 
versus C-Leg on Prosthesis Evaluation Questionnaire, stumbles, falls, walking tests, stair 
descent, and knee preference. J Rehabil Res Dev. 2008;45(1):1-14. 
30. 
van der Linde H, Hofstad CJ, Geurts AC, Postema K, Geertzen JH, van Limbeek J. A 
systematic literature review of the effect of different prosthetic components on human 
functioning with a lower-limb prosthesis. J Rehabil Res Dev. 2004;41(4):555-570. 
31. 
Andrysek J, Christensen J, Dupuis A. Factors influencing evidence-based practice in 
prosthetics and orthotics. Prosthet Orthot Int. 2011;35(1):30-38. 
32. 
Geil MD. Assessing the state of clinically applicable research for evidence-based practice 
in prosthetics and orthotics. J Rehabil Res Dev. 2009;46(3):305-313. 
33. 
Ramstrand N, Brodtkorb TH. Considerations for developing an evidenced-based practice in 
orthotics and prosthetics. Prosthet Orthot Int. 2008;32(1):93-102. 
34. 
Borrenpohl D, Kaluf B, Major MJ. Survey of US Practitioners on the Validity of the 
Medicare Functional Classification Level System and Utility of Clinical Outcome Measures 
for Aiding K-Level Assignment. Arch Phys Med Rehab. 2016;97(7):1053-1063. 
35. 
Chewning B, Bylund CL, Shah B, Arora NK, Gueguen JA, Makoul G. Patient preferences 
for shared decisions: a systematic review. Patient Educ Couns. 2012;86(1):9-18. 
36. 
Murray CD. 'Don't you talk to your prosthetist?' Communicational problems in the 
prescription of artificial limbs. Disabil Rehabil. 2013;35(6):513-521. 
37. 
Schaffalitzky E, NiMhurchadha S, Gallagher P, Hofkamp S, MacLachlan M, Wegener ST. 
Identifying the values and preferences of prosthetic users: a case study series using the 
repertory grid technique. Prosthet Orthot Int. 2009;33(2):157-166. 
38. 
Ostler C, Ellis-Hill C, Donovan-Hall M. Expectations of rehabilitation following lower limb 
amputation: a qualitative study. Disabil Rehabil. 2014;36(14):1169-1175. 
39. 
Sansam K, O'Connor RJ, Neumann V, Bhakta B. Clinicians' perspectives on decision 
making in lower limb amputee rehabilitation. J Rehabil Med. 2014;46(5):447-453. 
40. 
Dillingham TR, Pezzin LE, MacKenzie EJ, Burgess AR. Use and satisfaction with 
prosthetic devices among persons with trauma-related amputations: a long-term outcome 
study. Am J Phys Med Rehabil. 2001;80(8):563-571. 
41. 
Baars EC, Schrier E, Dijkstra PU, Geertzen JHB. Prosthesis satisfaction in lower limb 
amputees: A systematic review of associated factors and questionnaires. Medicine 
(Baltimore). 2018;97(39):e12296. 
42. 
Gailey R, McFarland LV, Cooper RA, et al. Unilateral lower-limb loss: prosthetic device use 
and functional outcomes in servicemembers from Vietnam war and OIF/OEF conflicts. J 
Rehabil Res Dev. 2010;47(4):317-331. 
43. 
Albrecht GL, Higgins PC. Rehabilitation success: the interrelationships of multiple criteria. J 
Health Soc Behav. 1978;18(1):36-45. 
44. 
Taenzer P, Melzack R, Jeans ME. Influence of psychological factors on postoperative pain, 
mood and analgesic requirements. Pain. 1986;24(3):331-342. 
45. 
Auer CJ, Glombiewski JA, Doering BK, et al. Patients' Expectations Predict Surgery 
Outcomes: A Meta-Analysis. Int J Behav Med. 2016;23(1):49-62. 
46. 
Gonzalez Saenz de Tejada M, Escobar A, Bilbao A, et al. A prospective study of the 
association of patient expectations with changes in health-related quality of life outcomes, 
following total joint replacement. BMC Musculoskelet Disord. 2014;15:248. 
47. 
Gonzalez Saenz de Tejada M, Escobar A, Herrera C, Garcia L, Aizpuru F, Sarasqueta C. 
Patient expectations and health-related quality of life outcomes following total joint 
replacement. Value Health. 2010;13(4):447-454. 
48. 
Cross M, Lapsley H, Barcenilla A, Parker D, Coolican M, March L. Patient expectations of 
hip and knee joint replacement surgery and postoperative health status. Patient. 
2009;2(1):51-60. 

Protocol Template 
Page 15 
CF-146, Effective 7/10/11 
 
49. 
Allen LA, McIlvennan CK, Thompson JS, et al. Effectiveness of an Intervention Supporting 
Shared Decision Making for Destination Therapy Left Ventricular Assist Device: The 
DECIDE-LVAD Randomized Clinical Trial. JAMA Intern Med. 2018;178(4):520-529. 
50. 
Stacey D, Legare F, Lewis K, et al. Decision aids for people facing health treatment or 
screening decisions. Cochrane Database Syst Rev. 2017;4:CD001431. 
51. 
Makoul G, Clayman ML. An integrative model of shared decision making in medical 
encounters. Patient Educ Couns. 2006;60(3):301-312. 
52. 
Ting HH, Brito JP, Montori VM. Shared decision making: science and action. Circ 
Cardiovasc Qual Outcomes. 2014;7(2):323-327. 
53. 
Hoffmann TC, Del Mar CB. Shared decision making: what do clinicians need to know and 
why should they bother? Med J Aust. 2014;201(9):513-514. 
54. 
Sepucha KR, Borkhoff CM, Lally J, et al. Establishing the effectiveness of patient decision 
aids: key constructs and measurement instruments. BMC Med Inform Decis Mak. 2013;13 
Suppl 2:S12. 
55. 
Rahman R. Comparison of Telephone and In-Person Interviews. Interdisciplinary 
Undergraduate Research Journal. 2015(Spring):10-13. 
56. 
Gill P, Stewart K, Treasure E, Chadwick B. Methods of data collection in qualitative 
research: interviews and focus groups. Br Dent J. 2008;204(6):291-295. 
57. 
Hennink MM, Kaiser BN, Weber MB. What Influences Saturation? Estimating Sample 
Sizes in Focus Group Research. Qualitative Health Research. 2019;29(10):1483-1496. 
58. 
Creswell JW, Poth CN. Qualitative inquiry & research design : choosing among five 
approaches. Fourth edition. ed. Los Angeles: SAGE; 2018. 
59. 
Degner LF, Sloan JA, Venkatesh P. The Control Preferences Scale. Can J Nurs Res. 
1997;29(3):21-43. 
60. 
Paige SR, Krieger JL, Stellefson M, Alber JM. eHealth literacy in chronic disease patients: 
An item response theory analysis of the eHealth literacy scale (eHEALS). Patient Educ 
Couns. 2017;100(2):320-326. 
61. 
van Tulder M, Furlan A, Bombardier C, Bouter L, Editorial Board of the Cochrane 
Collaboration Back Review G. Updated method guidelines for systematic reviews in the 
cochrane collaboration back review group. Spine (Phila Pa 1976). 2003;28(12):1290-1299. 
62. 
Quigley M, Dillon MP, Fatone S. Development of shared decision-making resources to help 
inform difficult healthcare decisions: An example focused on dysvascular partial foot and 
transtibial amputations. Prosthet Orthot Int. 2018;42(4):378-386. 
63. 
Coulter A, Stilwell D, Kryworuchko J, Mullen PD, Ng CJ, van der Weijden T. A systematic 
development process for patient decision aids. BMC Med Inform Decis Mak. 2013;13 
Suppl 2:S2. 
64. 
Elwyn G, Kreuwel I, Durand MA, et al. How to develop web-based decision support 
interventions for patients: a process map. Patient Educ Couns. 2011;82(2):260-265. 
65. 
Guest G, MacQueen KM, Namey EE. Applied thematic analysis. Los Angeles: Sage 
Publications; 2012. 
66. 
Ziegler-Graham K, MacKenzie EJ, Ephraim PL, Travison TG, Brookmeyer R. Estimating 
the prevalence of limb loss in the United States: 2005 to 2050. Arch Phys Med Rehab. 
2008;89(3):422-429. 
67. 
Starks H, Trinidad SB. Choose your method: a comparison of phenomenology, discourse 
analysis, and grounded theory. Qual Health Res. 2007;17(10):1372-1380. 
68. 
Matlock DD, Nowels CT, Masoudi FA, et al. Patient and cardiologist perceptions on 
decision making for implantable cardioverter-defibrillators: a qualitative study. Pacing Clin 
Electrophysiol. 2011;34(12):1634-1644. 
69. 
Jones J, Nowels C, Kutner JS, Matlock DD. Shared decision making and the use of a 
patient decision aid in advanced serious illness: provider and patient perspectives. Health 
Expect. 2015;18(6):3236-3247. 
70. 
Creswell JW, Plano Clark VL. Designing and conducting mixed methods research. Third 
Edition. ed. Los Angeles: SAGE; 2018. 
71. 
Matlock DD, Spatz ES. Design and testing of tools for shared decision making. Circ 
Cardiovasc Qual Outcomes. 2014;7(3):487-492. 

Protocol Template 
Page 16 
CF-146, Effective 7/10/11 
 
72. 
Moher D, Liberati A, Tetzlaff J, Altman DG, Group P. Preferred reporting items for 
systematic reviews and meta-analyses: the PRISMA statement. J Clin Epidemiol. 
2009;62(10):1006-1012. 
73. 
O'Connor AM, Bennett CL, Stacey D, et al. Decision aids for people facing health 
treatment or screening decisions. Cochrane Database Syst Rev. 2009(3):CD001431. 
74. 
Bowen DJ, Kreuter M, Spring B, et al. How We Design Feasibility Studies. American 
Journal of Preventive Medicine. 2009;36(5):452-457. 
75. 
Hsieh HF, Shannon SE. Three approaches to qualitative content analysis. Qual Health 
Res. 2005;15(9):1277-1288. 
76. 
Assarroudi A, Nabavi FH, Armat MR, Ebadi A, Vaismoradi M. Directed qualitative content 
analysis: the description and elaboration of its underpinning methods and data analysis 
process. J Res Nurs. 2018;23(1):42-55. 
77. 
Chopra A, Azarbal AF, Jung E, et al. Ambulation and functional outcome after major lower 
extremity amputation. J Vasc Surg. 2018;67(5):1521-1529. 
78. 
Gailey R. Predictive Outcome Measures Versus Functional Outcome Measures in the 
Lower Limb Amputee. J Prosthet Orthot. 2006;18(6):51-60.