Assessing the Acceptability and Feasibility of an mHealth App to Increase the Quantity and Quality of Physical Activity Experiences Among Individuals With Spinal Cord Injury Who Ambulate
Phase: NA
Conditions: Spinal Cord Injuries
Sponsor: University of British Columbia

 
                 Version 2: June 7 2021 
Page 1 of 17 
 
 
 
 
 
 
 
 
 
Research Proposal 
 
04/08/2021 
 
 
 
Study Title: SCI Step Together: Improving Physical Activity Participation Among Individuals 
 
 
 With SCI Who Ambulate 
 
 
Primary Investigator:  
Dr. Kathleen Martin Ginis (University of British Columbia) 
 
 
Co-investigators:  
Sarah Lawrason (University of British Columbia) 
 
 
 
Study Sites: 
1. University of British Columbia, Kelowna, BC, Canada 
 
 
Sponsors:  
Social Sciences and Humanities Research Council 
 
WorkSafe BC Research Training Award 
 
CDPP Funding 
 
 
 
 
 
 
 
 
 
 

 
                 Version 2: June 7 2021 
Page 2 of 17 
 
SUMMARY 
 
Purpose: To assess the feasibility and acceptability of a mobile health application (mHealth app) 
to increase quantity and quality of physical activity experiences among ambulators living with 
spinal cord injury. 
 
Justification: Individuals living with spinal cord injury (SCI) who walk participate in less 
physical activity than individuals with SCI who use wheelchairs. Lower levels of physical 
activity may be due to barriers such as increased pain and fatigue, lack of time, and lack of 
knowledge. Additionally, in the second study of my dissertation, we identified that action and 
coping planning, goal conflict, and skills are associated with increased physical activity levels. 
Quality of physical activity experiences also play an important role in participation. Recently, 
elements of positive and negative physical activity experiences, in addition to factors that 
influence quality, were classified among individuals with SCI who ambulate in the third study of 
my dissertation. These elements mapped onto the Quality Participation Framework (i.e., 
autonomy, belongingness, challenge, engagement, meaning, mastery) and the conditions aligned 
with the Quality Parasport Participation Framework (intrapersonal, social, program, and 
physical). Despite the recent focus on understanding factors that enhance both quantity and 
quality of physical activity participation, there are no physical activity interventions available 
targeted specifically for individuals with SCI who walk. Therefore, this study will develop and 
assess the acceptability and feasibility of a mHealth app to increase the quantity and quality of 
physical activity among ambulators with SCI according to evidence from the previous two 
studies. 
 
Objectives: The main objectives are to: (a) collaboratively develop and implement the 8-week 
program delivered through a mHealth app, (b) qualitatively evaluate the subjective experiences 
of the mHealth program (i.e., engagement, acceptability, and feasibility) and (c) quantitatively 
evaluate the engagement, acceptability, and feasibility, in addition to behaviour change factors, 
leisure-time physical activity levels, quality of physical activity participation, and employment. 
 
Study Design/Methods: This randomized controlled trial (RCT) will recruit a total of 20 
ambulators with SCI across Canada and the United States. Consenting participants will be 
randomized into either the wait-list control or intervention group. The wait-list control group will 
be asked to continue their everyday routine and not engage in any new physical activity or health 
program. The intervention group will participate in an 8-week program (also termed 
intervention) delivered through a mHealth app, consisting of education modules, worksheets, 
peer support and behavioural support. The intervention will aim to increase physical activity 
quantity and quality. Assessments will take place at baseline, 4-weeks, and 8-weeks for both the 
control and intervention groups. These assessments include social support, action control, basic 
psychological needs, autonomous motivation, behaviour change domains, leisure-time physical 
activity, quality of exercise and sport experiences, and employment hours and financial 
resources. After completing the final assessments at 8-weeks, participants in the intervention 
group will be invited to participate in an interview to get a better understanding of their 
satisfaction with the program. Only investigators on the study will have access to the de-
identified data, which will be stored on a password-protected folder in UBC’s One Drive. 
 

 
                 Version 2: June 7 2021 
Page 3 of 17 
 
Analyses: Demographic information will be used to describe the sample. Descriptive statistics 
will be used to characterize the sample using means and standard deviations for continuous 
variables and proportions and frequencies for categorical variables. Mixed effect models will be 
used to test for statistically significant different (p<0.05) in quantitative outcomes. Qualitative 
interviews will be transcribed, and a content analysis of the interview transcripts will be guided 
by an inductive approach. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 
                 Version 2: June 7 2021 
Page 4 of 17 
 
Table of Contents 
 
1. SUMMARY........................................................................................................................2 
2. BACKGROUND AND PROGRAM RATIONALE.......................................................5 
1.1 Physical activity among individuals with SCI who ambulate........................................5 
1.2 Quality participation in physical activity......................................................................5 
1.3 Physical activity intervention design and implementation............................................5 
3. PURPOSE & HYPOTHESES..........................................................................................6 
4. MEASURES.......................................................................................................................6 
5. RESEARCH DESIGN/PROTOCOL...............................................................................9 
6. RECRUITMENT.............................................................................................................10 
7. REMUNERATION..........................................................................................................11 
8. ADVERSE EVENTS.......................................................................................................11 
9. POTENTIAL BENEFITS...............................................................................................11 
10. DATA ANALYSIS...........................................................................................................12 
11. CONFIDENTIALITY.....................................................................................................12 
12. REFERENCES.................................................................................................................13 
 
 
 
 
 
 
 
 
 
 
 
 
 

 
                 Version 2: June 7 2021 
Page 5 of 17 
 
1. BACKGROUND AND PROGRAM RATIONALE 
 
1.1 Physical activity among individuals with SCI who ambulate 
 
Individuals living with SCI who ambulate participate in significantly less leisure-time 
physical activity (LTPA) than individuals with SCI who use a wheelchair (Martin Ginis et al., 
2010). Participation in low levels of LTPA may mean that ambulators with SCI are not obtaining 
the associated health benefits, such as increased cardiovascular fitness, or reduced pain and 
fatigue (DiPiro et al., 2016). This group may not be participating in LTPA due to unique barriers 
such as pain (Roberton et al., 2011), lack of group identity (Martin Ginis, Papathomas, et al., 
2017), lack of interest (Scelza et al., 2005), and lack of evidence-informed interventions to 
increase the quantity of LTPA participation. Recently, a cross-sectional study found that action 
and coping planning, goal conflict, and skills predict LTPA behaviour among ambulators with 
SCI (Lawrason & Martin Ginis, In press). Interventions informed by behaviour change theory 
that use strategies to target these behaviour change constructs could be valuable when aiming to 
increase the quantity of LTPA among ambulators with SCI. 
 
1.2 Quality participation in physical activity 
 
There is also a need to understand how to improve the quality of LTPA participation (i.e., 
subjective perceptions and experiences; Hammel et al., 2008) among ambulators with SCI. The 
quality of LTPA experiences may be important for improving well-being, health (Labbé et al., 
2019; McLean et al., 2014) and maintaining LTPA participation (Fong et al., 2020). A 
qualitative study using a pragmatic approach recently examined subjective experiences in LTPA 
among this population, informed by the Quality Participation Framework (Martin Ginis, Evans, 
et al., 2017) and the Quality Parasport Participation Framework (Evans et al., 2018) (Lawrason et 
al., In preparation). The study identified intrapersonal, social, program, and physical conditions 
that influence quality elements in LTPA (i.e., belongingness, meaning, mastery, engagement, 
challenge, and autonomy) (Lawrason et al., In preparation). These conditions may be targeted in 
an intervention to increase the quality of LTPA through behaviour change techniques such as 
goal setting (Michie et al., 2011). Behavioural support can increase quality through 
understanding the context of physical activity participation for ambulators with SCI, including 
experiences of ableism, feeling sidelined, and invisibility (Lawrason et al., In preparation). 
 
1.3 Physical activity intervention design and implementation  
 
Developing and implementing effective physical activity interventions requires a 
multifaceted approach. Using the person-based approach (Yardley, Ainsworth et al,. 2015) in 
combination with evidence, theory, and integrated knowledge translation (IKT, i.e., involving 
end-users throughout the research process; Graham et al., 2006) offers a unique and potentially 
impactful method for physical activity intervention development. To begin, the person-based 
approach aims to offer the groundwork for developing interventions which account for the 
context, perspectives, and lives of individuals who use them through mixed methods research 
(Yardley, Ainsworth, et al., 2015). As such, the person-based approach aligns well with IKT with 
the goal of involving end-users, and also with the concurrent use of theory and evidence 
(Yardley, Ainsworth et al., 2015). The person-based approach identifies strategies for 

 
                 Version 2: June 7 2021 
Page 6 of 17 
 
intervention planning, design, and development to ensure acceptability and feasibility for end-
users throughout and is thus ideal for digital health interventions (Yardley, Ainsworth, et al., 
2015; Yardley, Morrison et al., 2015).  
Interventions that are evidence- and theory-based and use IKT can improve physical activity 
outcomes among individuals with SCI (e.g., Ma et al., 2020). One such theory is self-
determination theory (SDT), which suggests that three basic needs are required for motivation 
and well-being: autonomy, competence, and relatedness (Ryan & Deci, 2000). SDT also posits 
that self-determined motivation lies on a spectrum from extrinsic (controlled) to intrinsic 
(autonomous) (Ryan & Deci, 2000). SDT aligns well with evidence from the study by Lawrason 
and Martin Ginis (In press) as planning can increase autonomous motivation (Sweet et al., 2017) 
and increasing competence through self-efficacy is a main goal (Ryan & Deci, 2000). Indeed, 
interventions can use behaviour change techniques that target SDT constructs (Sweet et al., 
2017). Furthermore, SDT is inherently aligned with the Quality Participation Framework (Martin 
Ginis, Evans, et al., 2017), as more intrinsically motivating (or self-determined) physical 
activities are likely to be higher quality. Finally, recent evidence suggests that an 8-week SDT-
informed telerehabilitation intervention can increase motivation and physical activity levels 
among individuals with SCI (Chemtob et al., 2019). Accordingly, using SDT may be a useful 
theory for informing a physical activity intervention that aims to increase quantity and quality of 
LTPA participation. Thus, we will use SDT as the framework to guide this intervention. 
Specifically, intervention components will target the three basic psychological needs in an effort 
to increase autonomous motivation to participate in LTPA (Ryan & Deci, 2000). 
 
PURPOSE & HYPOTHESIS 
 
Primary objective: The purpose of this project is to: (a) collaboratively develop and implement 
an intervention delivered through a mHealth app for persons with SCI who walk to increase the 
quantity and quality of physical activity, (b) evaluate the engagement, acceptability, and 
feasibility of the aforementioned intervention, and (c) assess primary outcomes of basic 
psychological needs, autonomous motivation, leisure-time physical activity levels, quality of 
physical activity participation, and employment. 
 
Hypotheses: The primary hypothesis is that the program will be deemed an acceptable and 
feasible method of improving physical activity participation among individuals with SCI who 
ambulate. A secondary hypothesis is that the program will improve basic psychological needs 
and autonomous motivation to participate in LTPA. A tertiary hypothesis is that the program will 
increase leisure-time physical activity levels, quality of physical activity participation, and 
employment. 
 
2. MEASURES (Appendix A) 
 
The following section on Feasibility and Engagement will not require any additional effort or 
information from participants, but rather assesses the study progression to understand whether 
the intervention is feasible for future implementation.   
 
Feasibility and Engagement 
 

 
                 Version 2: June 7 2021 
Page 7 of 17 
 
Feasibility will be assessed according to process, resource, management, and scientific 
indicators (Adamson et al., 2016; Learmonth & Motl, 2018). 
 
Process feasibility assesses participant recruitment. A recruitment rate (dividing the total number 
of participants enrolled by the number of participants contacted) and eligibility rate (number of 
potential participants excluded from the total number of interested participants) will be 
calculated. We will aim to have a recruitment rate of 60% and eligibility rate of 55% as reported 
by Jeske and colleagues (2020) in a physical activity intervention for individuals living with SCI.   
 
Resource feasibility assesses participation and monetary requirements of the study. Participation 
will be examined through retention rate (number of participants who completed at least some 
part of the intervention from those who were randomized) and adherence rate (number of 
participants who completed testing and follow-up measures). We will aim to have a retention 
rate of 90% (physical activity intervention for individuals with SCI; Jeske et al., 2020) to 100% 
(used at least one part of mobile health application; Smith et al., 2017) as reported by similar 
interventions. We will aim to have to have an adherence rate of 81-90% (Allin et al., 2020). We 
will assess the costs of the study as calculated by the total cost for producing the software and 
app, participant remuneration, and potential cost of the health behaviour coach.  
 
Management feasibility assesses data management and safety reporting during the study. We 
will record the IRB approval time according to the total number of days from submission to 
approval notification including any amendment details as necessary. Next, we will report staff 
preparation and reporting time calculated as the time to: recruit partners, conduct partner 
interviews, analyze recommendations, recruit participants, liaise with participants (e.g., group 
allocation, answering questions), and enter and check all participant data (i.e., total minutes). 
Missing data items (i.e., questions not answered for testing) will be monitored for baseline and 
follow-up assessments. 
 
Scientific feasibility assesses the safety, burden, and treatment effect of the study. Safety will be 
recorded as the number of health problems experienced by the participants over the course of the 
intervention. Demographic information will be established via a self-report questionnaire. We 
will describe measures for assessing participant satisfaction and burden below in the qualitative 
measures section. Compliance with the intervention will be calculated according to the number 
of participants who complete each weekly module. Although participant compliance is high for 
traditional physical activity interventions for people with SCI (88% to 91.7%; Brawley et al., 
2013; Jeske et al., 2020), we expect much lower compliance for an app-based intervention. 
Notably, one intervention states that compliance ranges from 16% to 100% depending on the 
module. As such, we expect to see different compliance rates throughout the course of the 
intervention. Finally, treatment effects will be assessed according to the quantitative measures 
listed below. 
 
Engagement with the app will be measured in different ways. First, we will measure compliance 
as stated above. Next, we will assess the number of times logged into the app over the course of 
8-weeks. Finally, we will look at how long each participant spends logged into the app during 
each module. Previous research suggests that web users spend significantly longer on 

 
                 Version 2: June 7 2021 
Page 8 of 17 
 
interventions compared to app users, but app users log into interventions significantly more times 
than web users (Morrison et al., 2018).  
 
Outcome Measures 
 
The Psychological Need Satisfaction in Exercise Scale: This 18-item scale assesses the 
satisfaction of the psychological needs for exercise using a 6-point Likert scale ranging from 1 
(false) to 6 (true) (Wilson et al., 2006). A mean can be calculated for each psychological need (6-
items each for autonomy, competence, and relatedness) with a higher score representing greater 
satisfaction of that need. The scale will be adapted by replacing “exercise” with “physical 
activity”. 
 
Social Support: Social support will be measured using a modified version of Sallis’ social 
support questionnaire (Sallis et al., 1987). The 7-item survey uses a 6-point Likert-type scale and 
assesses emotional support (3 items) and practical support (4 items). A similar version has been 
used in a similar intervention among individuals living with SCI and is sensitive to change in 
physical activity behaviour (Ma et al., 2019).  
 
The Treatment Self-Regulation for Exercise Scale (TSRES): The TSRES assesses 
autonomous and controlled motivation. The 15-item TSRES uses a 7-point Likert scale ranging 
from 1 (not at all true) to 7 (very true) to assess why one would engage in exercise activities 
(Levesque et al., 2007). The scale will be adapted by replacing “exercise” with “physical 
activity”. 
 
The Determinants of Physical Activity Questionnaire (DPAQ): This 33-item questionnaire is 
derived from Taylor et al. (2013) and based on the components of the Theoretical Domains 
Framework (Michie et al., 2008). This questionnaire aims to understand the behaviour change 
factors that influence LTPA among ambulators with SCI. A modified version will be used to 
assess the following domains targeted in the intervention: Knowledge, Beliefs about Capabilities, 
Skills, Social Influences, Beliefs about Consequences, Action Planning, Coping Planning, and 
Goal Conflict (24-items).  
 
Action Control: Action control will be assessed with six items that ask participants to indicate 
the extent to which they self-monitor their physical activity (1 = definitely false; 7 = definitely 
true) (Sniehotta et al., 2005). The scale has been demonstrated to be valid and reliable in 
individuals living with SCI. The scale will be adapted by replacing “exercise” with “physical 
activity”. 
 
The Leisure-Time Physical Activity Questionnaire-SCI (LTPAQ-SCI): The LTPAQ-SCI is a 
self-report recall measure administered by the student investigator to understand the frequency, 
duration, and intensity of LTPA performed over the previous seven days (Martin Ginis et al., 
2012). 
 
The Measure of Experiential Aspects of Participation (MeEAP): The MeEAP is a 
questionnaire to assess the six experiential aspects of participation (i.e., belongingness, meaning, 
mastery, engagement, challenge, and autonomy) across life domains (Caron et al., 2019). The 

 
                 Version 2: June 7 2021 
Page 9 of 17 
 
MeEAP is completed separately for each life domain with 12-items. Participants will be asked to 
complete the MeEAP for the exercise and sport domains only, for a total 24 items. Participants 
respond using a 7-point Likert type scale ranging from 1 (strongly disagree) and 7 (strongly 
agree). 
 
The Craig Handicap Assessment and Reporting Technique – Short Form (CHART-SF): 
The CHART-SF will be used to assess employment and financial resources (Whiteneck et al., 
1992). This questionnaire allows for both multiple choice and fill-in-the-blank answers. The 
CHART-SF will be modified to 2-items for the current study to only assess employment hours 
and financial earnings.  
 
Acceptability 
 
Semi-Structured Interview: After the final measurements at 8-weeks, participants from the 
intervention group will be invited to participate in an interview. This interview will allow the 
participant to provide feedback on the intervention with respect to satisfaction, burden, usability, 
and recommendations for future improvement. Previous interventions report high levels of 
satisfaction (Brawley et al., 2013), usability, and acceptability (Allin et al., 2020).  
 
3. RESEARCH DESIGN/PROTOCOL 
 
This randomized controlled trial will examine the feasibility and acceptability of a mHealth 
application called Stronger Together. Stronger Together is an app that hosts programs for 
individuals with chronic illnesses and disabilities. In this study, we are developing and testing the 
Stronger Together program that aims to improve the quantity and quality of physical activity 
among ambulators with SCI. Furthermore, the study will also collect pilot data on the magnitude 
of the effects on physical activity participation (quality and quantity) and psychosocial influences 
on physical activity. Individuals living with SCI who walk and live in Canada, or the United 
States will be recruited for this study and will be assigned to either a wait-list control or 
intervention group. The wait-list control group will be instructed to maintain their current health 
habits and that we would prefer them to not to engage in any new physical activity programs for 
the next 8-weeks. This is to ensure that potential program effects are independent of any other 
physical activity program, which is a standard protocol among physical activity randomized 
controlled trials. The wait-list control group will be invited to access the intervention after 8-
weeks. 
 
Potential participants will be immediately directed to complete the consent forms/baseline 
measures in Qualtrics. Once consent and baseline measures are completed, participants will be 
randomized into either the wait-list control or intervention condition. We will aim to recruit at 
least 8-10 participants with consent and baseline measures completed before randomization into 
conditions in order for there to be enough participants in the program at the same time for peer 
support. After the first 8-10 participants, we will randomize individuals immediately after 
baseline testing so that individuals randomized to the intervention group can join others in the 
app right away. Randomization will be done by Dr. Kathleen Martin Ginis using a random 
numbers generator in blocks of 2 and 4 with even groups in each condition (i.e., n=10 per 
condition). Waitlist-control participants will be directed to continue their normal daily activity. 

 
                 Version 2: June 7 2021 
Page 10 of 17 
 
Intervention participants will be directed to the App store to download the Stronger Together app 
to proceed with app registration. Participants will then be connected with the community coach 
who is a ‘real live person’ who monitors in-app activity (this will be the program lead, SL). 
Other in-app features include peer discussion groups, behavioural support, and educational 
modules to support strategies to increase the quantity and quality of physical activity.  
 
The 8-week program features weekly blocks of content. Each week builds from the previous 
week and targets specific components related to the three basic psychological needs (autonomy, 
relatedness, competence). The overall cadence of each weekly block is maintained throughout. 
For example, each week contains: 1) education modules 2) a worksheet or guided practice to 
apply the strategies in their own goals for that week along with embedded questions to discuss 
with their community coach 3) behavioural support from the community coach and 4) peer 
support from the discussion group. Participants in the intervention group will be encouraged to 
use the app as often as needed (but at least once per week) and actively participate in the 
programming. The community coach (SL) will prompt participants who have not engaged in the 
app in a week to remind them to complete weekly modules. In-app data, including user metrics 
will be collected and analyzed for descriptive patterns and assess correlations with the outcome 
measures (e.g., is the amount of time spent in-app correlated with changes in behaviour). 
 
Participants in both the intervention and control groups will be asked to participate in eight 
online questionnaires provided through the survey platform Qualtrics at three different time 
points (baseline/onboarding, 4- and 8-weeks of using the Stronger Together program). A link to 
these questionnaires which will be hosted on Qualtrics will be emailed to all participants. 
Participants in both groups will also complete a 5-minute demographic questionnaire at the 
beginning (baseline) of the study. Outcome measure included in the online surveys will include 
the following: basic psychological needs (The Psychological Need Satisfaction in Exercise 
Scale); autonomous and controlled motivation (The Treatment Self-Regulation for Exercise 
Scale); social support (Sallis et al., 1987); action control (Sniehotta et al., 2005); behaviour 
change constructs (Determinants of Physical Activity Questionnaire); leisure-time physical 
activity (LTPAQ-SCI); quality participation (MeEAP); and employment (CHART-SF).  
 
After completing the final online survey (at 8-weeks), participants in the intervention group will 
be invited to participate in an interview to further explore their experiences and to increase our 
understanding of factors that influence acceptability and satisfaction of the Stronger Together 
program. The interview will be structured whereby the participant will go through the application 
with the interviewer to discuss components that they liked and disliked. This will provide a 
greater understanding of user engagement. Interviews will take place through video conferencing 
software. The interviews will be audio recorded to transcribe and code for analyses. The 
interviewer will confirm their consent verbally at the start of the interview. 
 
Additionally, feasibility metrics will be kept and recorded by the program lead (SL) throughout 
the duration of the study. These metrics are related to process, resource, management, and 
scientific feasibility. More information on the feasibility metrics can be found in the research 
proposal (Appendix A). 
 
4. RECRUITMENT 

 
                 Version 2: June 7 2021 
Page 11 of 17 
 
 
Inclusion Criteria 
Potential participants will be selected for the study if they: 
- 
Can read and write in English 
- 
Own a smartphone or tablet 
- 
Are 19 years of age or older 
- 
Are a Canadian or United States resident 
- 
Have sustained a spinal cord injury 
- 
Are greater than 1 year post spinal cord injury 
- 
Walk for their daily mode of mobility (do not use a wheelchair for daily mode of 
mobility) 
 
This study will attempt to recruit a total of 20 individuals with SCI who ambulate in Canada 
or the United States. Recruitment will happen through open channels such as social media and 
word of mouth. The program lead (SL) will approach eligible groups that may be interested in 
the program through email and social media channels (i.e., Instagram, Facebook, Twitter) using 
the recruitment letter and/or poster. Community organizations that have members who have 
expressed interest in participating in SCI research studies will be emailed. These organizations 
will provide postings and communications through newsletters, postings on Facebook, and 
emails to members. Dr. Kathleen Martin Ginis is affiliated with community organizations whom 
will be contacted. Information about the study will also be posted to the International 
Collaboration on Repair Discoveries (iCORD) community newsletter and website for 
recruitment. 
 
Individuals who identify themselves as potential participants will be directed to complete an 
online consent and enrolment form via Qualtrics. This form details the inclusion and exclusion 
criteria for participants. Eligible participants will then receive an email from Qualtrics on behalf 
of the program regarding the next steps and how to download the app to get started. Once 
participants have joined the Stronger Together platform on their smartphone, they will be guided 
through an onboarding procedure, and connected with the community coach. Other in-app 
features include peer discussion groups, behavioural support, and educational modules to support 
strategies to increase the quantity and quality of physical activity. 
 
5. REMUNERATION 
 
Participants will be incentivized to complete questionnaires through compensation. Participants 
can receive up to $100 for partaking in this study if they complete all questionnaires and the 
interview. Participants will be compensated for completing questionnaires at each time point: 
$20 at time 1 (baseline), $30 at time 2 (week 4), and $40 at time 3 (week 8). If participants 
complete all questionnaires at all time points, they will receive $90. If they partake in the 
interview, they will receive an additional $10.  
 
6. ADVERSE EVENTS 
 
We do not think there is anything in the study that could harm or be bad for the participants. 
However, the following may happen in the study: Questionnaires, interview and intervention 

 
                 Version 2: June 7 2021 
Page 12 of 17 
 
programming: Occasionally, answering questions about feelings and experiences may make 
participants feel uncomfortable. Participants are not required to answer all of the questions and 
may skip any that make them feel uncomfortable or bring up any of their concerns. 
Participants that do experience an emotional reaction (e.g., distress) during programming, 
surveys or interviews will receive a list of resources that they may access (e.g., for mental health 
concerns). There is also a live coach who monitors the app and can respond directly to 
participants who have concerns. 
 
It is possible that the actions taken to achieve set goals (as encouraged by the weekly 
content) may lead to an adverse event (e.g., a fall during walking that results in a fracture, if 
increased walking was something that the participant wanted to do). During the consent process, 
participants will be advised that if such a situation occurs to receive medical attention and to 
report such instances to the project coordinator. Additionally, during the consent process, 
individuals will be advised that information provided by the health coach should not be 
prioritized over advice given by their health professionals, and that if they have such concerns 
that this should be raised with the health coach, and if not resolved then with the project 
coordinator. 
 
7. POTENTIAL BENEFITS 
 
The Stronger Together program may have the potential to improve physical activity and 
related health behaviours and may reduce the risks of developing a chronic disease or underlying 
health issue. The program may also improve self-management strategies, as it represents a low-
cost, easily mobilized, and proactive approach to ensure positive physical activity participation 
among ambulators with spinal cord injury, especially during the COVID-19 pandemic. The 
information we gather will also be of benefit to people organizing leisure-time physical activity 
programs for people living with spinal cord injuries and for other people in the future who will 
participate. 
 
8. DATA ANALYSIS 
 
Demographic information will be used to describe the sample. Descriptive statistics will be 
used to characterize the sample using means and standard deviations for continuous variables 
and proportions and frequencies for categorical variables. Mixed effects models will be used to 
test for statistically significant different (p<0.05) in quantitative outcomes. Qualitative interviews 
will be transcribed, and a content analysis of the interview transcripts will be guided by an 
inductive approach 
 
9. CONFIDENTIALITY 
 
All electronic files will be saved in a password protected folder on UBC’s One Drive. All 
electronic files and devices containing personal information about an identifiable individual 
collected for the purposes of this study will be encrypted. All data that is downloaded from 
the password-protected Qualtrics survey platform will be entered into processing (e.g. excel) 
and statistical software (SPSS). These electronic files will be saved in a password-protected 
folder on UBC’s One Drive. The contact information for each participant will be stored in 

 
                 Version 2: June 7 2021 
Page 13 of 17 
 
the master participant file database, only accessible by the study PI, co-investigators and 
study staff. This file will be password-protected and saved in a password-protected folder on 
UBC’s One Drive in a separate location from the data files. This contact information will not 
be linked to files that contain responses to the study outcomes. 
 
Interviews will occur over UBC licensed Zoom and the servers for these are located in 
Canada. Digital audio recordings of interviews will be transferred to a secure file storage in a 
password-protected folder on UBC’s One Drive. Once transferred, the recording will 
immediately be deleted from the computer on which the recording was made. Recordings 
will be deleted once the interview transcripts have been checked for accuracy and 
anonymized. 
 
The Stronger Together platform is privacy and regulatory compliant. More information 
about Curatio's privacy policy can be found here: https://www.curatio.me/privacy. The 
following statement is copied from Curatio’s privacy notice: Curatio uses service providers 
located in Canada and countries other than Canada, including the United States, to deliver 
Stronger Together. These other countries may have different privacy laws than Canada and 
your personal information may not be as well protected as it is under Canadian privacy law. 
In the US, data is subject to the US Patriot Act. We have updated the letter of information 
and consent form to include a clickable link that directs them to Curatio’s full privacy notice 
through this link which they can access before consenting to study participation. Participants 
also have the right to withdraw themselves from the study should they feel their personal 
information is unsafe. 
 
The information collected at registration is the user's email, password and user/display name. 
The researchers would not have the ability to remove the information. The information is owned 
and governed by the users themselves. 
 
The consent forms and questionnaires will be administered via Qualtrics. Qualtrics is a 
cloud-based service contracted by UBC. The survey information collected using this tool is 
stored in Toronto, Ontario and backed up in Montreal, Quebec. 
 
All data will be accessible via Curatio and Qualtrics. This data will be patient-provided 
(e.g. email address, name - if chosen to provide in app). This data will not be identifiable, 
unless the patient chooses to disclose/share their personal information. We will inform 
participants that they can sign up with their email address and choose a display name that is not 
connected to themselves (pseudonym), and also choose not to provide any more personal 
information about themselves. Data from questionnaire responses will be tied to the user’s 
profile in the app in order to connect any changes in their responses to their in app activity. 
However, data from the questionnaires and the in app activity data will be stored using a 
participant ID that is not connected to any of their personal information shared in app. 
 
 
 
 

 
                 Version 2: June 7 2021 
Page 14 of 17 
 
10. REFERENCES 
 
Adamson, B. C., Learmonth, Y. C., Kinnett-Hopkins, D., Bohri, M., & Motl, R. W. (2016). 
 
Feasibility study design and methods for Project GEMS: Guidelines for Exercise in 
 
Multiple Sclerosis. Contemporary Clinical Trials, 47, 32-39. 
 
https://doi.org/10.1016/j.cct.2015.12.002 
 
Allin, S., Shepherd, J., Thorson, T., Tomasone, J., Munce, S., Linassi, G., McBride, C. B., 
 
Jiancaro, & Jaglal, S. (2020). Web-based health coaching for spinal cord injury: Results 
 
from a mixed methods feasibility evaluation. JMIR Rehabilitation and Assistive 
 
Technologies, 7(2), e16351. https://doi.org/10.2196/16351 
  
Brawley, L. R., Arbour-Nicitopoulos, K. P., & Martin Ginis, K. A. (2013). Developing physical 
 
activity interventions for adults with spinal cord injury. Part 3: A pilot feasibility study of 
 
an intervention to increase self-managed physical activity. Rehabilitation Psychology, 
 
58(3), 316-321. http://dx.doi.org/10.1037/a0032814 
 
Caron, J. G., Martin Ginis, K. A., Rocchi, M., & Sweet, S. N. (2019). Development of the 
 
Measure of Experiential Aspects of Participation for people with physical disabilities. 
 
Archives of Physical Medicine and Rehabilitation, 100(1), 67-77. 
 
https://doi.org/10.1016/j.apmr.2018.08.183 
 
Chemtob, K., Rocchi, M., Arbour-Nicitopoulos, K., Kairy, D., Fillion, B., & Sweet, S. N. (2019). 
 
Using tele-health to enhance motivation, leisure time physical activity, and quality of life 
 
in adults with spinal cord injury: A self-determination theory-based pilot randomized 
 
control trial. Psychology of Sport and Exercise, 43, 243-252. 
 
https://doi.org/10.1016/j.psychsport.2019.03.008 
 
DiPiro, N. D., Embry, A. E., Fritz, S. L., Middleton, A., Krause, J. S., & Gregory, C. M. (2016). 
 
Effects of aerobic exercise training on fitness and walking-related outcomes in 
 
ambulatory individuals with chronic incomplete spinal cord injury. Spinal Cord, 54(9), 
 
675–81. https://doi.org/ 10.1038/sc.2015.212 
 
Evans, M. B., Shirazipour, C. H., Zanhour, M., Sweet, S. N., Martin Ginis, K. A., & Latimer-
 
Cheung, A. E. (2018). Integrating insights from the parasport community to understand 
 
optimal Experiences: The Quality Parasport Participation Framework. Psychology of 
 
Sport and Exercise, 37, 79-90. https://doi.org/10.1016/j.psychsport.2018.04.009 
 
Fong, A. J., Saxton, H. R., Kauffeldt, K. D., Sabiston, C. M., & Tomasone, J. R. (2020). “We’re 
 
all in the same boat together”: Exploring quality participation strategies in dragon boat 
 
teams for breast cancer survivors. Disability and Rehabilitation, 1-12. 
 
https://doi.org/10.1080/09638288.2020.1733676 
 
Graham, I. D., Logan, J., Harrison, M. B., Straus, S. E., Tetroe, J., Caswell, W., & Robinson, N. 
 
(2006). Lost in knowledge translation: time for a map? The Journal of Continuing 
 
Education in the Health Professions, 26(1), 13–24. http://doi.org/10.1002/chp.47 

 
                 Version 2: June 7 2021 
Page 15 of 17 
 
 
Hammel, J., Magasi, S., Heinemann, A., Whiteneck, G., Bogner, J., & Rodriguez, E. (2008). 
 
What does participation mean? An insider perspective from people with disabilities. 
 
Disability and Rehabilitation, 30(19), 1445-1460. https://doi-
 
org/10.1080/09638280701625534 
 
Jeske, S. J. D., Brawley, L. R., & Arbour-Nicitopoulos, K. P. (2020). Videoconference-delivered 
 
group-based physical activity self-regulatory support for adults with spinal cord injury: A 
 
feasibility study. Adapted Physical Activity Quarterly, 37(3), 270-288. https://doi-org 
 
/10.1123/apaq.2019-0103 
 
Labbé, D., Miller, W. C., & Ng, R. (2019). Participating more, participating better: Health 
 
benefits of adaptive leisure for people with disabilities. Disability and Health Journal, 
 
12(2), 287-295. https://doi.org/10.1016/j.dhjo.2018.11.007 
 
Lawrason, S. V. C., & Martin Ginis, K. A. (In press). Factors associated with leisure-time 
 
physical activity participation among individuals with spinal cord injury who ambulate. 
 
Disability and Rehabilitation, 1-8.  
 
Lawrason, S. V. C., Tomasone, J. R., Olsen, K., & Martin Ginis, K. A. (In preparation). “I’m 
 
glad I can walk, but sometimes it’s so challenging that it’s an inconvenience to myself 
 
and others”: Physical activity experiences among individuals with spinal cord injury who 
 
ambulate. To be submitted to Qualitative Research in Sport, Exercise, & Health.  
 
Learmonth, Y. C., & Motl, R. W. (2018). Important considerations for feasibility studies in 
 
physical activity research involving persons with multiple sclerosis: a scoping systematic 
 
review and case study. Pilot and Feasibility Studies, 4(1), 1-11. 
 
https://doi.org/10.1186/s40814-017-0145-8 
 
Levesque, C. S., Williams, G. C., Elliot, D., Pickering, M. A., Bodenhamer, B., & Finley, P. J. 
 
(2007). Validating the theoretical structure of the Treatment Self-Regulation 
 
Questionnaire (TSRQ) across three different health behaviors. Health Education 
 
Research, 22(5), 691-702. https://doi.org/10.1093/her/cyl148 
 
Ma, J. K., Cheifetz, O., Todd, K. R., Chebaro, C., Phang, S. H., Shaw, R. B., Whaley, K. J., & 
 
Martin Ginis, K. A. (2020). Co-development of a physiotherapist-delivered physical 
 
activity intervention for adults with spinal cord injury. Spinal Cord, 58, 778-786. 
 
https://doi.org/10.1038/s41393-020-0422-x 
 
Ma, J. K., West, C. R., & Martin Ginis, K. A. (2019). The effects of a patient and provider co-
 
developed, behavioral physical activity intervention on physical activity, psychosocial 
 
predictors, and fitness in individuals with spinal cord injury: A randomized controlled 
 
trial. Sports Medicine, 49, 1117-1131. https://doi.org/10.1007/s40279-019-01118-5 
 
Martin Ginis, K. A., Latimer, A. E., Arbour-Nicitopoulos, K. P., Buchholz, A. C., Bray, S. 
 
R., Craven, B. C., … Wolfe, D. L. (2010). Leisure time physical activity in a population-

 
                 Version 2: June 7 2021 
Page 16 of 17 
 
 
based sample of people with spinal cord injury part I: demographic and injury-related 
 
correlates. Archives of Physical Medicine and Rehabilitation, 91(5), 722–8. 
 
https://doi.org/10.1016/j.apmr.2009.12.027 
 
Martin Ginis, K. A., Phang, S. H., Latimer, A. E., & Arbour-Nicitopoulos, K. P. (2012). 
 
Reliability and validity tests of the Leisure Time Physical Activity Questionnaire for 
 
People with Spinal Cord Injury. Archives of Physical Medicine and Rehabilitation, 93(4), 
 
677-682. https://doi.org/10.1016/j.apmr.2011.11.005 
 
Martin Ginis, K. A., Papathomas, A., Perrier, M. J., Smith, B., & SHAPE-SCI Research Group. 
 
(2017). Psychosocial factors associated with physical activity in ambulatory and manual 
 
wheelchair users with spinal cord injury: A mixed-methods study. Disability and 
 
Rehabilitation, 39(2), 187-192. https://doi.org/10.3109/09638288.2015.1045991 
 
Martin Ginis, K. A., Evans, M. B., Mortenson, W. B., & Noreau, L. (2017). Broadening the 
 
conceptualization of participation of persons with physical disabilities: A configurative 
 
review and recommendations. Archives of Physical Medicine and Rehabilitation, 98(2), 
 
395-402. https://doi.org./10.1016/j.apmr.2016.04.017 
 
McLean, A. M., Jarus, T., Hubley, A. M., & Jongbloed, L. (2014). Associations between social 
 
participation and subjective quality of life for adults with moderate to severe traumatic 
 
brain injury. Disability and Rehabilitation, 36(17), 1409-1418. https://doi-
 
org/10.3109/09638288.2013.834986 
 
Michie, S., Johnston, M., Francis, J., Hardeman, W., & Eccles, M. (2008). From theory to 
 
intervention: Mapping theoretically derived behavioural determinants to behaviour 
 
change techniques. Applied Psychology, 57(4), 660-680. https://doi.org./10.1111/j.1464-
 
0597.2008.00341.x 
 
Michie, S., van Stralen, M.M., & West, R. (2011). The behaviour change wheel: A new method 
 
for characterizing and designing behaviour change interventions. Implementation 
 
Science, 6(1), 42. https://doi.org./10.1186/1748-5908-6-42 
 
Morrison, L. G., Geraghty, A. W. A., Lloyd, S., Goodman, N., Michaelides, D. T., Hargood, C., 
 
Weal, M., & Yardley, L. (2018). Comparing usage of a web and app stress management 
 
intervention: An observational study. Internet Interventions, 12, 74-82. 
 
https://doi.org/10.1016/j.invent.2018.03.006 
 
Roberton, T., Bucks, R. S., Skinner, T. C., Allison, G. T., & Dunlop, S. A. (2011). Barriers to 
 
physical activity in individuals with spinal cord injury: A Western Australian study. The 
 
Australian Journal of Counselling, 17(2), 74-88. 
 
Ryan, R. M., & Deci, E. L. (2000). Self-determination theory and the facilitation of intrinsic 
 
motivation, social development, and well-being. American Psychologist, 55(1), 68-78.  
 

 
                 Version 2: June 7 2021 
Page 17 of 17 
 
Sallis, J. F., Grossman, R. M., Pinski, R. B., Patterson, T. L., & Nader, P. R. (1987). The 
 
development of scales to measure social support for diet and exercise behaviors. 
 
Preventive Medicine, 16(6), 825-836. https://doi.org/10.1016/0091-7435(87)90022-3 
 
Scelza, W. M., Kalpakjian, C. Z., Zemper, E. D., & Tate, D. G. (2005). Perceived barriers to 
 
exercise in people with spinal cord injury. American Journal of Physical Medicine & 
 
Rehabilitation, 84(8), 576-583. https://doi.org/10.1097/01.phm.0000171172.96290.67 
 
Smith, E., Bradbury, K., Scott, L., Steele, M., Little, P., & Yardley, L. (2017). Providing online 
 
weight management in Primary Care: a mixed methods process evaluation of healthcare 
 
practitioners’ experiences of using and supporting patients using POWeR+. 
 
Implementation Science, 12, 69. https://doi.org/10.1186/s13012-017-0596-6 
 
Sniehotta, F. F., Scholz, U., & Schwarzer, R. (2005). Bridging the intention–behaviour gap: 
 
Planning, self-efficacy, and action control in the adoption and maintenance of physical 
 
exercise. Psychology & Health, 20(2), 143-160. 
 
https://doi.org/10.1080/08870440512331317670 
 
Sweet, S. N., Rocchi, M., Arbour-Nicitopoulos, K., Kairy, D., & Fillion, B. (2017). A 
 
telerehabilitation approach to enhance quality of life through exercise among adults with 
 
paraplegia: Study protocol. JMIR Research Protocols, 6(10), e202. 
 
https://doi.org./10.2196/resprot.8047 
 
Taylor, N., Lawton, R., & Conner, M. (2013). Development and initial validation of the 
 
determinants of physical activity questionnaire. International Journal of Behavioral 
 
Nutrition and Physical Activity, 10, 74. https://doi.org/10.1186/1479-5868-10-74 
 
Whiteneck, G. G., Charlifue, S. W., Gerhart, K. A., Overholser, J. D., & Richardson, G. N. 
 
(1992). Quantifying handicap: A new measure of long-term rehabilitation outcomes. 
 
Archives of Physical Medicine and Rehabilitation, 73(6), 519-526. 
 
https://doi.org/10.5555/uri:pii:000399939290185Y 
 
Wilson, P. M., Rogers, W. T., Rodgers, W. M., Wild, T. C. (2006). The Psychological Need 
 
Satisfaction in Exercise Scale. Journal of Sport and Exercise Psychology, 28(3), 231-251. 
 
https://doi.org/10.1123/jsep.28.3.231 
 
Yardley, L., Ainsworth, B., Arden-Close, E., & Muller, I. (2015). The person-based approach to 
 
enhancing the acceptability and feasibility of interventions. Pilot and Feasibility Studies, 
 
1, 37. https://doi.org/10.1186/s40814-015-0033-z 
 
Yardley, L., Morrison, L., Bradbury, K., & Muller, I. (2015). The person-based approach to 
 
intervention development: Application to digital health-related behavior change 
 
interventions. Journal of Medicine and Internet Research, 17(1), e30. 
 
https://doi.org/10.2196/jmir.4055