Effective of Online Physical Activity Monitoring in Inflammatory Arthritis (OPAM-IA): A New Model of Care
Phase: NA
Conditions: Joint Diseases, Rheumatoid Arthritis, Systemic Lupus Erythematosus
Sponsor: University of British Columbia

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Study protocol and statistical analysis plan 
 
Date: October 9, 2017 
 
Citation:  
Li LC, Feehan LM, Shaw C, Xie H, Sayre EC, Aviña-Zubeita A, Grewal N, Townsend AF, 
Gromala D, Noonan G, Backman CL. A technology-enabled counselling program versus a 
delayed treatment control to support physical activity participation in people with inflammatory 
arthritis: Study protocol for the opam-ia randomized controlled trial. BMC Rheumatol 2017;1:6. 
https://bmcrheumatol.biomedcentral.com/articles/10.1186/s41927-017-0005-4  
 
 

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BACKGROUND 
Arthritis is the most common cause of severe chronic pain and disability worldwide [1,2].  
Promoting physical activity is a priority because it is an essential adjunct to medical treatment 
for people with inflammatory arthritis (e.g., rheumatoid arthritis [RA]; systemic lupus 
erythematosus [SLE]) [3,4], partly due to its effects in reducing risks of cardiovascular 
conditions and metabolic syndromes [5-8].  Physical activity level is also inversely associated 
with inflammatory markers such as C-reactive protein level and erythrocyte sedimentation rate in 
people with RA [6-8].  For people with SLE, physical activity is important due to its positive 
effect on sleep quality [9] and fatigue [10,11], which is the most prevalent and debilitating 
symptom [12].  
Public health guidelines recommend at least 150 minutes a week of moderate/vigorous 
physical activity (MVPA), performed in bouts of 10 or more minutes [13].  However, the 
majority of people with arthritis do not meet the recommendations. The Canadian Community 
Health Survey reported that over 57% of people with arthritis were physically inactive during 
their leisure time, compared to 46% of those without arthritis [14].  A 2012 study using 
accelerometers found 42% of those with RA [15] accumulated 0 minute (in bouts) of MVPA in 
the preceding 7 days. The poor level of participation in physical activity in these populations 
represent a major knowledge-to-action gap. 
  
Several modifiable risk factors are associated with low physical activity participation in 
people with arthritis. These include lack of motivation [16], doubts about the effectiveness of 
exercise [17], and lack of health professional advice [18].  Once patients start being active, they 
need feedback on their progress. A Cochrane review reported that ‘graded exercise activity’, 
which initially focuses on simple activities and then gradually increase to more challenging ones, 
is effective for improving adherence in people with chronic musculoskeletal condition [19]. 

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Progression of activities can be guided by a physical therapist (PT) [19].  However, this is 
challenging to implement because only some parts of Canada have access to publicly funded 
arthritis-trained PTs for consultation [20].  The current knowledge on physical activity 
participation highlights the need for a new model of care that enables patients to monitor their 
activity performance, obtain feedback from health professionals and receive motivational support 
across geographic locations. 
 
Study Aim and Hypotheses 
 
This study aims to determine whether a technology-enabled physical activity counselling 
intervention can improve physical activity participation in people with RA or SLE. We 
hypothesize that, compared to controls, those who receive the 8-week intervention will: 1) 
increase mean daily MVPA time as determined by an objective measure, 2) reduce mean daily 
sedentary time during waking hours, 3) have less pain, 4) have less fatigue, and 5) improve in 
perceived self-management capacity. In addition, we will explore the effect of the interventions 
on depressive symptoms and habitual behaviours.  
 
Study Design 
The Effectiveness of Online Physical Activity Monitoring in Inflammatory Arthritis 
(OPAM-IA) project will employ a mix of quantitative and qualitative research methods.  The 
intervention will be evaluated in a randomized controlled trial (RCT) with a delayed control 
design, whereby participants will be randomly assigned to start the intervention either 
immediately or at Week 10 (Figure 1).  This design is particularly suitable when the proposed 
intervention is likely to do more good than harm, as it allows all participants to receive the 
intervention by the end of the study. After completing the intervention, participants will partake 

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in an in-depth interview by phone regarding their experiences.  We have previously 
demonstrated feasibility of the study protocol in 34 people with osteoarthritis, with no dropout 
and 88% adhered to the protocol [21,22].  In addition, we observed preliminary efficacy, with 
those who received the intervention showing a trend of improvement in MVPA and perceived 
self-management capacity compared to the controls after 1 month [22].  
 
Insert Figure 1: CONSORT flow diagram 
 
METHODS 
Participants 
Eligible participants will be recruited from the Mary Pack Arthritis Program (Vancouver 
Coastal Health Authority) and Fraser Health Authority in British Columbia, Canada.  Study 
information will also be posted on social media (Facebook, Twitter, Kajiji, Craigslist).  
Individuals are eligible if they have a diagnosis of RA or SLE, have an email address and daily 
access to internet, and are able to attend the 1.5-hour education session.  We will exclude people 
who have previously used any physical activity wearables or are unsafe to be physically active 
without health professional supervision, as identified by the Physical Activity Readiness 
Questionnaire (PAR-Q) [23].  
After completing the baseline measures, participants will be randomly assigned to the 
Immediate Group or the Delayed Group (i.e. control) in 1:1 allocation ratio. Randomization, 
stratified by diagnosis (RA or SLE), will be performed using numbers generated by SAS v9.4 
(SAS Institute, Cary, North Carolina, USA) in variable block sizes to ensure adequate allocation 
concealment.  
 

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Wearable and Online Technology 
The intervention will include a Fitbit Flex 2TM wristband.  Fitbit® is a commercial 
wearable device which tracks and displays steps walked, gross level of physical exertion, and the 
time spent being active.  Fitbit® has an open source platform that permits customization of a new 
app, FitViz, to enhance the use of the data as part of our activity coaching strategy.  To ensure 
user friendliness, FitViz was co-developed with 3 patient research partners from Arthritis 
Research Canada and Arthritis Consumer Experts.  Using FitViz, the participant can share 
information with a study PT who will coach them to set activity goals by phone and adjust the 
activity parameters in the app remotely.  These parameters include: 1) the upper and lower bound 
of intensity and duration of MVPA, 2) the duration when a sedentary behaviour should be 
interrupted, and 3) the rest time in between vigorous activities (i.e., pacing).  By combining the 
use of a wearable, an app and coaching from a PT, we maximize the use of behavioural change 
techniques for supporting people with arthritis to engage in an active lifestyle [24].  
 
Intervention 
The Immediate Group will receive the 8-week intervention immediately after 
randomization.  Participants will attend a 1.5-hour session where they receive: 1) 20 minutes of 
standardized education about physical activity, 2) a Fitbit Flex 2TM and a FitViz app account, and 
3) individual coaching by a study PT trained in motivational interviewing [25].  The coaching 
will follow the Brief Action Planning approach [26], whereby the PT guides individuals to set 
goals, develop an action plan, and identify barriers and solutions.  The PT will then adjust the 
activity parameters on the app based on the participants’ goals. 
Participants’ physical activity will be captured continuously by the Fitbit® and wirelessly 
synchronized with FitViz 150 times/day.  During Weeks 1-8, a study PT will review participants’ 

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progress and coach them to modify their physical activity goals via 4 biweekly phone calls.  A 
counselling guide will be used and the discussion will be documented by the PT.  Participants 
may also contact the PT via email with questions.  At the end of the intervention, participants 
may keep their Fitbit® and FitViz account, but will have no contact with a PT. 
The Delayed Group will receive the intervention in Week 10.  During the waiting period 
(Delayed Group only) or post-intervention period, participants will receive monthly emails of 
arthritis news, which are unrelated to physical activity. 
To better understand the reasons people do or do not adopt and maintain recommended 
levels of physical activity, we will interview we will interview 20 participants with RA and 20 
with SLE for 1 hour by phone after the intervention.  Interviews will focus on 1) goals set, 
strategies used, barriers/facilitators to being active, 2) their experience with the intervention, 3) 
the nature of activities they engage in, and 4) their experience of being a research participant.  
These data will enrich the RCT data, and inform the design of the future implementation 
strategy, if the intervention is found to be effective. 
 
Outcome measures 
Participants will be assessed at baseline (T0), and Weeks 9 (T1), 18 (T2) and 27 (T3).  
Our primary outcome measure will be mean daily MVPA time measure with SenseWear Mini, a 
multi-sensor monitor that is worn on the upper arm over the triceps.  It integrates tri-axial 
accelerometer data, physiological sensor data and personal demographic information to provide 
estimates of steps and energy expenditure.  Tierney et al [27] has showed that SenseWear is a 
valid tool for estimating energy expenditure during activities of daily living in people with RA 
(ICC=0.72). A strong relationship was also found between SenseWear and indirect calorimetry 
measures of energy expenditure for activities of daily living (Pearson's r=0.85) [27].  SenseWear 

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can be worn 24 hours a day.  Hence, it can capture a full picture of physical activity and the off-
body time throughout the day [28,29].  An important feature of SenseWear is its ability to 
differentiate between sedentary and light physical activities [30], making it an ideal instrument to 
assess both active and sedentary behaviours.  Participants will wear a SenseWear Mini for 7 days 
at each assessment.  Almeida et al [31] determined that a minimum of 4 days of wear is required 
to reliably assess energy expenditure from different levels of physical activity in people with RA 
(ICC > .80).  
We will calculate the average daily MVPA accumulated in bouts per day.  A bout is 
defined as >10 consecutive minutes at the level of >3 METs (i.e., the lower bound of MVPA), 
with allowance for interruption of up to 2 minutes below the threshold [32].  Additional analysis 
will be performed with a cut-off at >4 METs which reflects purposeful activities [33]. 
Secondary outcomes will measure 1) mean daily time in sedentary behaviour, 2) average 
daily step count, 3) McGill Pain Questionnaire Short Form (MPQ-SF), 4) Fatigue Severity Scale, 
and 5) Partners in Health Scale.  Sedentary behaviour and step count will be measured with 
SenseWear.  For sedentary behaviour, we will calculate the mean daily time spent with an energy 
expenditure of <1.5 METs, occurring in bouts of >20 minutes during waking hours [34-37].  The 
MPQ-SF contains 15 pain-related words, which can be rated from 0 to 3 (higher=more severe) 
[38].  The Fatigue Severity Scale, which consists of 9 questions measuring the impact of fatigue, 
has demonstrated excellent internal consistency (Cronbach’s α=0.89) [12].  Construct validity 
was demonstrated by a moderate correlation with pain (r=0.68) and depression (r=0.46) [39].  
The Partners in Health Scale is a 12-item measure designed to assess self-efficacy, knowledge of 
health conditions and treatment, and self-management behaviour such as adopting a healthy 
lifestyle (Cronbach’s α=0.82) [40].  

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Tertiary outcome will include Patient Health Questionnaire-9 (PHQ-9) [41] and Self-
Reported Habit Index [40].  The PHQ-9 consists of 9 questions (rated from 0 to 3) that 
correspond to the diagnostic criteria for major depressive disorder. A total score of greater than 
11 indicates a major depressive disorder [41].  A difference of at least 5 points indicates clinical 
change over time [42].  The Self-Reported Habit Index is a 12-item scale, rated on a 7-point 
Likert scale, that measures characteristics of habitual behavior (reliability minimum α=0.81). We 
will ask participants to rate their strength of habit for 3 specific activity-related behaviors: sitting 
during leisure time at home, sitting during usual occupational activities, and walking outside for 
10 minutes.  A higher score indicates a stronger habit or behaviour that is done frequently and 
automatically [43,44].  
 
Data Analysis and Monitoring 
Power calculation 
Our collaboration with health authorities and patient groups will allow the study to recruit 
130 eligible participants within 24 months.  In one of our proof-of-concept studies on a similar 
physical activity counselling intervention involving 61 people with osteoarthritis, we estimated a 
standard deviation (SD) of 52.0 minutes of bouted MVPA performed in sessions of > 10 minutes 
(unpublished data).  Assuming an attrition rate of approximately 15%, we anticipate 110 of the 
130 participants will complete the study (55 per group).  With a sample size of 110 and α-level 
of 0.05, we will have 80.5% power to detect a between-group difference of at least 25 minutes 
post intervention (via one-sided test). 
 
Intervention Fidelity and Adverse Event Monitoring 

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We will monitor intervention fidelity by tracking participants’ Fitbit/FitViz app usage 
statistics (frequency & duration of use) during the evaluation periods.  Further, we will analyze 
PTs’ physical activity counselling records to ensure the discussions follow the brief action 
planning approach.  Participants will report any serious adverse events (falls, cardiovascular and 
musculoskeletal events) [45] to the study coordinator at any time during the study period. In 
addition, we will ask participants to record all adverse events related to their physical activity in 
the follow-up questionnaire at Weeks 9, 18 and 27.   
 
Data Analysis 
An intention-to-treat analysis will be performed by a biostatistician who is blinded to the 
group assignment.  For the main comparison, we will use the Shapiro-Wilk test to assess 
normality of the outcome variables.  If normality assumption is rejected a suitable transformation 
will be selected to achieve an approximately normal distribution [46].  Analysis of covariance 
(ANCOVA) will be used to evaluate the effect of the intervention on the outcome measures, 
adjusting for 2 strata and blocking.  If blocking is found to play no role, then it will be removed 
from the subsequent analyses. 
Since we expect the randomization schedule to be implemented as planned, any 
differences between groups at baseline should be due to chance. Hence, the main analysis will 
not adjust for baseline differences [47,48].  We will perform sensitivity analyses to adjust for 
baseline differences that appear to be clinically important to determine if they affect the 
conclusion from the main analysis.  The first contrast will compare T0-T1 between the 2 groups 
to determine if the intervention is superior to the control.  The second contrast will compare T0-
T1 with T1-T2 in the Delayed Group.  Unlike the first contrast which provides between-subjects 
treatment effect estimate, this second contrast uses within-subject pre-post comparison for 

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treatment effect estimates.  We will use linear mixed-effects longitudinal models to combine the 
first and second contrast for an overall treatment effect estimation.  This combined estimate has 
the potential to substantially improve the precision of treatment effect estimates as compared 
with using either one alone.  The third contrast will compare T0–T1 in the Immediate Group 
against T1-T2 in the Delayed Group.  The forth contrast will compare T0-T1 in the Immediate 
Group against T1-T3 in the Delayed Group.  The last two models will assess if the 10-week 
delay had an impact on the efficacy of the intervention.  We will use descriptive analysis to 
summarize participant characteristics, comorbid conditions and adverse events, which will be 
adjudicated by the first author. 
For the qualitative interviews, we will conduct an iterative content analysis, whereby 
codes will be identified and revised as interviews are analyzed.  Initial open coding (i.e., 
assigning conceptual labels to the content) will be followed by clustering the labels into thematic 
categories.  Quotes representative of the thematic categories will be identified to illustrate 
participants' perspectives on physical activity, nature of activities, and their experiences as 
research participants.  These data will inform the interpretation of statistical analyses and the 
design of future studies and implementation strategies, for example, ways for PTs to provide 
feedback about physical activity to people with inflammatory arthritis.  
 
ABBREVIATIONS 
ANCOVA: Analysis of Covariance 
ICC: Intraclass Correlation 
MPQ-SF: McGill Pain Questionnaire Short Form 
MVPA: Moderate-to-Vigorous Physical Activity 
OPAM: Effectiveness of Online Physical Activity Monitoring in Inflammatory Arthritis Project 

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PAR-Q: Physical Activity Readiness Questionnaire 
PHQ-9: Patient Health Questionnaire-9 
PT: Physical Therapist 
RA: Rheumatoid Arthritis 
RCT: Randomized Controlled Trial 
SLE: Systemic Lupus Erythematosus 
SD: Standard Deviation 

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