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A technology-enabled Counselling program versus a delayed treatment control to support physical activity… Li, Linda C; Feehan, Lynne M; Shaw, Chris; Xie, Hui; Sayre, Eric C; Aviña-Zubeita, Antonio; Grewal, Navi; Townsend, Anne F; Gromala, Diane; Noonan, Greg; Backman, Catherine L Nov 28, 2017

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STUDY PROTOCOL Open AccessA technology-enabled Counselling programFitViz, to track and obtain feedback about their physical activity, 3) receive 4 biweekly follow-up calls from the PT.Those in the Delayed Group will receive the same program in Week 10. We will interview a sample of participantsill not be, individualsne if thisto aCT02554474.BMC RheumatologyLi et al. BMC Rheumatology  (2017) 1:6 DOI 10.1186/s41927-017-0005-4Road, Richmond, BC V6X 2C7, CanadaFull list of author information is available at the end of the article1Department of Physical Therapy, University of British Columbia, FriedmanBuilding, 2177 Wesbrook Mall, Vancouver, BC, Canada2Arthritis Research Canada, Milan Ilich Arthritis Research Centre, 5591 No. 3sedentary behaviour, pain, fatigue, mood, self-management capacity, and habitual behaviour.Discussion: A limitation of this study is that participants, who also administer the outcome measures, wblinded. Nonetheless, by customizing existing self-monitoring technologies in a patient-centred mannercan be coached to engage in an active lifestyle and monitor their performance. The results will determiintervention improves physical activity participation. The qualitative interviews will also provide insight inparadigm to integrate this program to support self-management.Trial registration: Date of last update in ClinicalTrials.gov: September 18, 2015. ClinicalTrials.gov Identifier: NKeywords: Physical activity, Arthritis, Wearables, Behavioural interventions, Counselling* Correspondence: lli@arthritisresearch.caabout their experiences with the intervention. Participants will be assessed at baseline, and Weeks 9, 18 and 27. Theprimary outcome measure is time spent in moderate/vigorous physical activity in bouts of ≥ 10 min, measured witha portable multi-sensor device in the free-living environment. Secondary outcomes include step count, time inversus a delayed treatment control tosupport physical activity participation inpeople with inflammatory arthritis: studyprotocol for the OPAM-IA randomizedcontrolled trialLinda C. Li1,2*, Lynne M. Feehan1, Chris Shaw3, Hui Xie2,4, Eric C. Sayre2, Antonio Aviña-Zubeita2,5, Navi Grewal2,Anne F. Townsend2,6, Diane Gromala3, Greg Noonan7 and Catherine L. Backman2,8AbstractBackground: Being physically active is an essential component of successful self-management for people withinflammatory arthritis; however, the vast majority of patients are inactive. This study aims to determine whethera technology-enabled counselling intervention can improve physical activity participation and patient outcomes.Methods: The Effectiveness of Online Physical Activity Monitoring in Inflammatory Arthritis (OPAM-IA) projectis a community-based randomized controlled trial with a delayed control design. We will recruit 130 people withrheumatoid arthritis or systemic lupus erythematosus, who can be physically active without health professionalsupervision. Randomization will be stratified by diagnosis. In Weeks 1–8, participants in the Immediate Group will: 1)receive education and counselling by a physical therapist (PT), 2) use a Fitbit and a new web-based application,© The Author(s). 2017 Open Access This articInternational License (http://creativecommonsreproduction in any medium, provided you gthe Creative Commons license, and indicate if(http://creativecommons.org/publicdomain/zele is distributed under the terms of the Creative Commons Attribution 4.0.org/licenses/by/4.0/), which permits unrestricted use, distribution, andive appropriate credit to the original author(s) and the source, provide a link tochanges were made. The Creative Commons Public Domain Dedication waiverro/1.0/) applies to the data made available in this article, unless otherwise stated.Li et al. BMC Rheumatology  (2017) 1:6 Page 2 of 8BackgroundArthritis is the most common cause of severe chronic painand disability worldwide [1, 2]. Promoting physical activityis a priority because it is an essential adjunct to medicaltreatment for people with inflammatory arthritis (e.g.,rheumatoid arthritis [RA]; systemic lupus erythematosus[SLE]) [3, 4], partly due to its effects in reducing risksof cardiovascular conditions and metabolic syndromes[5–8]. Physical activity level is also inversely associatedwith inflammatory markers such as C-reactive proteinlevel and erythrocyte sedimentation rate in people withRA [6–8]. For people with SLE, physical activity is im-portant due to its positive effect on sleep quality [9]and fatigue [10, 11], which is the most prevalent anddebilitating symptom [12].Public health guidelines recommend at least 150 min aweek of moderate/vigorous physical activity (MVPA),performed in bouts of 10 or more minutes [13]. How-ever, the majority of people with arthritis do not meetthe recommendations. The Canadian Community HealthSurvey reported that over 57% of people with arthritis werephysically inactive during their leisure time, compared to46% of those without arthritis [14]. A 2012 study using ac-celerometers found 42% of those with RA [15] accumu-lated 0 min (in bouts) of MVPA in the preceding 7 days.The poor level of participation in physical activity inthese populations represent a major knowledge-to-action gap.Several modifiable risk factors are associated with lowphysical activity participation in people with arthritis.These include lack of motivation [16], doubts about theeffectiveness of exercise [17], and lack of health profes-sional advice [18]. Once patients start being active, theyneed feedback on their progress. A Cochrane review re-ported that ‘graded exercise activity’, which initially fo-cuses on simple activities and then gradually increase tomore challenging ones, is effective for improving adher-ence in people with chronic musculoskeletal condition[19]. Progression of activities can be guided by a physicaltherapist (PT) [19]. However, this is challenging to im-plement because only some parts of Canada have accessto publicly funded arthritis-trained PTs for consultation[20]. The current knowledge on physical activity par-ticipation highlights the need for a new model of carethat enables patients to monitor their activity per-formance, obtain feedback from health professionalsand receive motivational support across geographiclocations.Study aim and hypothesesThis study aims to determine whether a technology-enabled physical activity counselling intervention canimprove physical activity participation in people withRA or SLE. We hypothesize that, compared to controls,those who receive the 8-week intervention will: 1) in-crease mean daily MVPA time as determined by an ob-jective measure, 2) reduce mean daily sedentary timeduring waking hours, 3) have less pain, 4) have lessfatigue, and 5) improve in perceived self-managementcapacity. In addition, we will explore the effect of theinterventions on depressive symptoms and habitualbehaviours.Study designThe Effectiveness of Online Physical Activity Monitoringin Inflammatory Arthritis (OPAM-IA) project will em-ploy a mix of quantitative and qualitative researchmethods. The intervention will be evaluated in a ran-domized controlled trial (RCT) with a delayed controldesign, whereby participants will be randomly assignedto start the intervention either immediately or at Week10 (Fig. 1). This design is particularly suitable when theproposed intervention is likely to do more good thanharm, as it allows all participants to receive the interven-tion by the end of the study. After completing the in-tervention, participants will partake in an in-depthinterview by phone regarding their experiences. We havepreviously demonstrated feasibility of the study protocolin 34 people with osteoarthritis, with no dropout and88% adhered to the protocol [21, 22]. In addition, we ob-served preliminary efficacy, with those who received theintervention showing a trend of improvement in MVPAand perceived self-management capacity compared tothe controls after 1 month [22].MethodsParticipantsEligible participants will be recruited from the Mary PackArthritis 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) and distributed byour patient pratner's organizations (Arthritis ResearchCanada, and Arthritis Consumer Experts). Individuals areeligible if they have a diagnosis of RA or SLE, have anemail address and daily access to internet, and are able toattend the 1.5-h education session. We will exclude peoplewho have previously used any physical activity wearablesor are unsafe to be physically active without health profes-sional supervision, as identified by the Physical ActivityReadiness Questionnaire (PAR-Q) [23].After completing the baseline measures, participantswill be randomly assigned to the Immediate Group orthe Delayed Group (i.e. control) in 1:1 allocation ratio.Randomization, stratified by diagnosis (RA or SLE), willbe performed using numbers generated by SAS v9.4(SAS Institute, Cary, North Carolina, USA) in variableblock sizes to ensure adequate allocation concealment.Li et al. BMC Rheumatology  (2017) 1:6 Page 3 of 8Wearable and online technologyThe intervention will include a Fitbit Flex 2™ wristband.Fitbit® is a commercial wearable device which tracksand displays steps walked, gross level of physical exer-tion, and the time spent being active. Fitbit® has anopen source platform that permits customization of anew app, FitViz, to enhance the use of the data as partof our activity coaching strategy. To ensure user friend-liness, FitViz was co-developed with 3 patient researchpartners from Arthritis Research Canada and ArthritisConsumer Experts. Using FitViz, the participant canshare information with a study PT who will coach themto set activity goals by phone and adjust the activityparameters in the app remotely. These parametersFig. 1 CONSORT flow diagraminclude: 1) the upper and lower bound of intensity andduration of MVPA, 2) the duration when a sedentarybehaviour should be interrupted, and 3) the rest time inbetween vigorous activities (i.e., pacing). By combiningthe use of a wearable, an app and coaching from a PT,we maximize the use of behavioural change techniquesfor supporting people with arthritis to engage in an ac-tive lifestyle [24].InterventionThe Immediate Group will receive the 8-week interven-tion immediately after randomization. Participants willattend a 1.5-h session where they receive: 1) 20 min ofstandardized education about physical activity, 2) a FitbitLi et al. BMC Rheumatology  (2017) 1:6 Page 4 of 8Flex 2™ and a FitViz app account, and 3) individualcoaching by a study PT trained in motivational interview-ing [25]. The coaching will follow the Brief Action Plan-ning approach [26], whereby the PT guides individuals toset goals, develop an action plan, and identify barriers andsolutions. The PT will then adjust the activity parameterson the app based on the participants’ goals.Participants’ physical activity will be captured continu-ously by the Fitbit® and wirelessly synchronized withFitViz 150 times/day. During Weeks 1–8, a study PTwill review participants’ progress and coach them tomodify their physical activity goals via 4 biweekly phonecalls. A counselling guide will be used and the discussionwill be documented by the PT. Participants may alsocontact the PT via email with questions. At the end ofthe intervention, participants may keep their Fitbit® andFitViz account, but will have no contact with a PT.The Delayed Group will receive the intervention inWeek 10. During the waiting period (Delayed Group only)or post-intervention period, participants will receivemonthly emails of arthritis news, which are unrelated tophysical activity.To better understand the reasons people do or do notadopt and maintain recommended levels of physical ac-tivity, we will interview 20 participants with RA and 20with SLE for 1 h by phone after the intervention. Inter-views will focus on 1) goals set, strategies used, barriers/facilitators to being active, 2) their experience with theintervention, 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 de-sign of the future implementation strategy, if the inter-vention is found to be effective.Outcome measuresParticipants will be assessed at baseline (T0), and Weeks 9(T1), 18 (T2) and 27 (T3). Our primary outcome measurewill be mean daily MVPA time measure with SenseWearMini, a multi-sensor monitor that is worn on the upperarm over the triceps. It integrates tri-axial accelerometerdata, physiological sensor data and personal demographicinformation to provide estimates of steps and energy ex-penditure. Tierney et al. [27] has showed that SenseWearis a valid tool for estimating energy expenditure during ac-tivities of daily living in people with RA (ICC = 0.72). Astrong relationship was also found between SenseWearand indirect calorimetry measures of energy expenditurefor activities of daily living (Pearson’s r = 0.85) [27]. Sense-Wear can be worn 24 h a day. Hence, it can capture a fullpicture of physical activity and the off-body time through-out the day [28, 29]. An important feature of SenseWearis its ability to differentiate between sedentary and lightphysical activities [30], making it an ideal instrument toassess both active and sedentary behaviours. Participantswill wear a SenseWear Mini for 7 days at each assessment.Almeida et al. [31] determined that a minimum of 4 daysof wear is required to reliably assess energy expenditurefrom different levels of physical activity in people with RA(ICC > .80).We will calculate the average daily MVPA accumulatedin bouts per day. A bout is defined as ≥ 10 consecutive mi-nutes at the level of ≥ 3 METs (i.e., the lower bound ofMVPA), with allowance for interruption of up to 2 minbelow the threshold [32]. Additional analysis will be per-formed with a cut-off at ≥ 4 METs which reflects purpose-ful activities [33].Secondary outcomes will measure 1) mean daily timein sedentary behaviour, 2) average daily step count, 3)McGill Pain Questionnaire Short Form (MPQ-SF), 4) Fa-tigue Severity Scale, and 5) Partners in Health Scale.Sedentary behaviour and step count will be measuredwith SenseWear. For sedentary behaviour, we will calcu-late the mean daily time spent with an energy expend-iture of ≤ 1.5 METs, occurring in bouts of > 20 minduring waking hours [34–37]. The MPQ-SF contains 15pain-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 offatigue, has demonstrated excellent internal consistency(Cronbach’s α = 0.89) [12]. Construct validity was dem-onstrated by a moderate correlation with pain (r = 0.68)and depression (r = 0.46) [39]. The Partners in HealthScale 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].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 de-pressive disorder. A total score of greater than 11 indi-cates a major depressive disorder [41]. A difference ofat 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 charac-teristics of habitual behavior (reliability minimum α =0.81). We will ask participants to rate their strength ofhabit for 3 specific activity-related behaviors: sittingduring leisure time at home, sitting during usual occu-pational activities, and walking outside for 10 min. Ahigher score indicates a stronger habit or behaviourthat is done frequently and automatically [43, 44].Data analysis and monitoringPower calculationOur collaboration with health authorities and patientgroups will allow the study to recruit 130 eligible partici-pants within 24 months. In one of our proof-of-conceptin the Delayed Group. The forth contrast will compareLi et al. BMC Rheumatology  (2017) 1:6 Page 5 of 8studies on a similar physical activity counselling inter-vention involving 61 people with osteoarthritis, we esti-mated a standard deviation (SD) of 52.0 min of boutedMVPA performed in sessions of ≥ 10 min (unpublisheddata). Assuming an attrition rate of approximately 15%,we anticipate 110 of the 130 participants will completethe study (55 per group). With a sample size of 110 andα-level of 0.05, we will have 80.5% power to detect abetween-group difference of at least 25 min post inter-vention (via one-sided test).Intervention Fidelity and adverse event monitoringWe will monitor intervention fidelity by tracking partici-pants’ Fitbit/FitViz app usage statistics (frequency & dur-ation of use) during the evaluation periods. Further, wewill analyze PTs’ physical activity counselling records toensure the discussions follow the brief action planningapproach. Participants will report any serious adverseevents (falls, cardiovascular and musculoskeletal events)[45] to the study coordinator at any time during thestudy period. In addition, we will ask participants to rec-ord all adverse events related to their physical activity inthe follow-up questionnaire at Weeks 9, 18 and 27.Data analysisAn intention-to-treat analysis will be performed by abiostatistician who is blinded to the group assignment.For the main comparison, we will use the Shapiro-Wilktest to assess normality of the outcome variables. If nor-mality assumption is rejected a suitable transformationwill be selected to achieve an approximately normal dis-tribution [46]. Analysis of covariance (ANCOVA) will beused to evaluate the effect of the intervention on theoutcome measures, adjusting for 2 strata and blocking.If blocking is found to play no role, then it will be re-moved from the subsequent analyses.Since we expect the randomization schedule to beimplemented as planned, any differences betweengroups at baseline should be due to chance. Hence, themain analysis will not adjust for baseline differences[47, 48]. We will perform sensitivity analyses to adjustfor baseline differences that appear to be clinically im-portant to determine if they affect the conclusion fromthe main analysis. The first contrast will compare T0-T1 between the 2 groups to determine if the interven-tion is superior to the control. The second contrast willcompare T0-T1 with T1-T2 in the Delayed Group. Un-like the first contrast which provides between-subjectstreatment effect estimate, this second contrast useswithin-subject pre-post comparison for treatment effectestimates. We will use linear mixed-effects longitudinalmodels to combine the first and second contrast for anoverall treatment effect estimation. This combined esti-mate has the potential to substantially improve theDiscussionPotential impact and significance of the studyMore than 1 in 6 people in the U.S. are using wearabledevices to monitor their health [49], but the integrationof these tools in chronic disease management is still atan early stage. The OPAM project will evaluate a noveltechnology-enabled physical activity counselling inter-vention that adapts a popular wearable device to motiv-ate and provide feedback to people with inflammatoryarthritis regardless of their location. If shown to be ef-fective, this intervention could inform a new person-centred approach to optimize self-management amongpeople with arthritis. Furthermore, since being active isa key component of successful self-management, thisintervention has potential to improve disease-relatedoutcome and quality of life. Although RA and SLE areour current focus, the FitViz app is designed to beadaptable and scalable to serve people with otherchronic diseases and to address other aspects of self-management (e.g., adding a self-report module to trackmedication use).Strengths and weaknesses of the studyThis study has several strengths. Frist, we have previ-ously demonstrated feasibility to deliver the remoteT0-T1 in the Immediate Group against T1-T3 in theDelayed Group. The last two models will assess if the10-week delay had an impact on the efficacy of the inter-vention. We will use descriptive analysis to summarizeparticipant characteristics, comorbid conditions andadverse events, which will be adjudicated by the firstauthor.For the qualitative interviews, we will conduct an it-erative content analysis, whereby codes will be identi-fied and revised as interviews are analyzed. Initialopen coding (i.e., assigning conceptual labels to thecontent) will be followed by clustering the labels intothematic categories. Quotes representative of the the-matic categories will be identified to illustrate partici-pants’ perspectives on physical activity, nature ofactivities, and their experiences as research partici-pants. These data will inform the interpretation ofstatistical analyses and the design of future studiesand implementation strategies, for example, ways forPTs to provide feedback about physical activity topeople with inflammatory arthritis.precision of treatment effect estimates as comparedwith using either one alone. The third contrast willcompare T0–T1 in the Immediate Group against T1-T2counselling intervention to our target population with ahigh level of adherence to the protocol [22]. Second,the PT counselling will ensure intervention fidelity,tice, if it is shown to be effective.Li et al. BMC Rheumatology  (2017) 1:6 Page 6 of 8A limitation of the study is that the intervention re-quires participants to use the device continuously for8 weeks. To minimize non-compliance, we choose touse Fitbit Flex 2™ which can be worn on the wrist 24 ha day including during water-based activities. Our pilotstudy suggests that it is feasible for people with jointpain to use the device continuously for an extendedperiod [22]. Also, it is possible that participants maygain access to a Fitbit during the non-interventionperiod since it is commercially available. To encourageadherence to the study protocol, participants may keeptheir device after the study period free of charge. FitVizwill only be available to study participants through thestudy. We believe that these measures will minimizethe risk of contamination in the RCT.Supporting a physically active lifestyle is a corebusiness of the physical therapy profession. The Exer-cise is Medicine initiative currently advocates for thecreation and implementation of effective physical ac-tivity counselling strategies in treatment plans for pa-tients around the world [50]. With the ubiquitous useof wearables and the popularity of the quantified-selfmovement [51], health professionals can now leveragethe engaging power of technology to motivate, moni-tor and counsel patients living with chronic disease.PTs are in the position to lead in the effort to create,evaluate and integrate technology to improve physicalactivity participation of patients. To this end, theOPAM project will be a first step to generate the ne-cessary evidence on this type of PT-led interventionto support patient self-management.AbbreviationsANCOVA: Analysis of Covariance; ICC: Intraclass Correlation; MPQ-SF: McGill PainQuestionnaire Short Form; MVPA: Moderate-to-Vigorous Physical Activity;OPAM-IA: Effectiveness of Online Physical Activity Monitoring in InflammatoryArthritis Project; PAR-Q: Physical Activity Readiness Questionnaire; PHQ-9: PatientHealth Questionnaire-9; PT: Physical Therapist; RA: Rheumatoid Arthritis;RCT: Randomized Controlled Trial; SD: Standard Deviation; SLE: Systemic LupusErythematosusAcknowledgementsWe are grateful for the partnership and support of patient/consumerwhich is important for maintaining internal validity ofthe study and enhancing external validity. Third, therigorous mixed-methods design will enhance our abilityto develop strategies to integrate this program in peo-ple’s daily life in the future. Finally, we anticipate thatthe pragmatic nature of the program will improve thechance of successful implementation in clinical prac-our process to monitor participants’ Fitbit/FitViz use andcollaborators, including Alison Hoens and Kelly English (Arthritis ResearchCanada, Arthritis Patient Advisory Board), as well as Cheryl Koehn (ArthritisConsumer Experts).FundingThis study is supported by The Arthritis Society (Funding Reference Number:SOG-14-110).Availability of data and materialsNot applicable.Authors’ contributionsLCL, LMF, CS, HX, ECS, AA, AFT, DG, GN, CLB have made substantialcontributions to the study design. LCL, LMF, NG have contributed to theongoing data collection. All listed authors have contributed to the draftingof the manuscript. All authors read and approved the final manuscript.Authors’ informationDr. Linda Li is supported by the Harold Robinson/Arthritis Society Chair inArthritic Diseases award, the Canada Research Chair Program, and theMichael Smith Foundation for Health Research (MSFHR) Scholar Award.Dr. Hui Xie is supported by the Maureen and Milan Ilich / Merck Chair inStatistics for Arthritis and Musculoskeletal Diseases award. Dr. AntonioAviña-Zubeita is supported the BC Lupus Association Scholar Award and theMSFHR Scholar Award. Dr. Diane Gromala is supported by the CanadaResearch Chair Program.Ethics approval and consent to participateThe research protocol has been approved by the University of BritishColumbia Clinical Research Ethics Board (H15–01843), and published inClinicalTials.gov (NCT02554474). Written consent will be obtained from allparticipants.Consent for publicationNot applicable.Competing interestsThe authors declare that they have no competing interests.Publisher’s NoteSpringer Nature remains neutral with regard to jurisdictional claims in publishedmaps and institutional affiliations.Author details1Department of Physical Therapy, University of British Columbia, FriedmanBuilding, 2177 Wesbrook Mall, Vancouver, BC, Canada. 2Arthritis ResearchCanada, Milan Ilich Arthritis Research Centre, 5591 No. 3 Road, Richmond, BCV6X 2C7, Canada. 3School of Interactive Arts and Technology, Simon FraserUniversity, 250-13450 102 Avenue, Surrey, BC V3T 0A3, Canada. 4Faculty ofHealth Sciences, Simon Fraser University, 8888 University Drive, Burnaby, BC,Canada. 5Department of Medicine, University of British Columbia, 2775 LaurelStreet, 10th Floor, Vancouver, BC V5Z 1M9, Canada. 6Medical School,University of Exeter, St Luke’s Campus, Heavitree Road, Exeter EX1 2LU, UK.7Mary Pack Arthritis Program, Vancouver General Hospital, 895 W 10thAvenue, Vancouver, BC, Canada. 8Department of Occupational Therapy andOccupational Science, University of British Columbia, 2211 Wesbrook MallT325, Vancouver, BC V6T 2B5, Canada.Received: 2 October 2017 Accepted: 19 October 2017References1. 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