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“Not just another walking program”: Everyday Activity Supports You (EASY) model—a randomized pilot study… Ashe, Maureen C; Winters, Meghan; Hoppmann, Christiane A; Dawes, Martin G; Gardiner, Paul A; Giangregorio, Lora M; Madden, Kenneth M; McAllister, Megan M; Wong, Gillian; Puyat, Joseph H; Singer, Joel; Sims-Gould, Joanie; McKay, Heather A Jan 12, 2015

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RESEARCH Open Access“Not just another walking program”: Everydayfollowing screening, 68% (56/82) met the inclusion criteria and 45% (25/56) were randomized by remote web-basedallocation. This included 13 participants in the intervention group and 12 participants in the control group (education).Ashe et al. Pilot and Feasibility Studies 2015, 1:4http://www.pilotfeasibilitystudies.com/content/1/1/4320-5950 University Boulevard, Vancouver, BC V6T 1Z3, CanadaFull list of author information is available at the end of the articleAt 6 months, 12/13 (92%) intervention and 8/12 (67%) control participants completed the final assessment. Controllingfor baseline values, the intervention group had an average of 2,080 [95% confidence intervals (CIs) 704, 4,918] moresteps/day at 6 months compared with the control group. There was an average between group difference in weightloss of −4.3 [95% CI −6.22, −2.40] kg and reduction in diastolic blood pressure of −8.54 [95% CI −16.89, −0.198] mmHg,in favor of EASY.Conclusions: The EASY pilot study was feasible to deliver; there was an increase in physical activity and reduction inweight and blood pressure for intervention participants at 6 months.(Continued on next page)* Correspondence: Maureen.Ashe@ubc.ca1Centre for Hip Health and Mobility, 7F-2635 Laurel Street, Vancouver, BCV5Z 1 M9, Canada2Department of Family Practice, University of British Columbia (UBC),Activity Supports You (EASY) model—arandomized pilot study for a parallel randomizedcontrolled trialMaureen C Ashe1,2*, Meghan Winters1,3, Christiane A Hoppmann1,4, Martin G Dawes2, Paul A Gardiner5,6,Lora M Giangregorio7, Kenneth M Madden1,8, Megan M McAllister1,2, Gillian Wong1,2, Joseph H Puyat9,10,Joel Singer9,10, Joanie Sims-Gould1,2 and Heather A McKay1,2,11AbstractBackground: Maintaining physical activity is an important goal with positive health benefits, yet many peoplespend most of their day sitting. Our Everyday Activity Supports You (EASY) model aims to encourage movementthrough daily activities and utilitarian walking. The primary objective of this phase was to test study feasibility(recruitment and retention rates) for the EASY model.Methods: This 6-month study took place in Vancouver, Canada, from May to December 2013, with data analyses inFebruary 2014. Participants were healthy, inactive, community-dwelling women aged 55–70 years. We recruited throughadvertisements in local community newspapers and randomized participants using a remote web service. The modelincluded the following: group-based education and social support, individualized physical activity prescription (calledActivity 4-1-1), and use of a Fitbit activity monitor. The control group received health-related information only. The mainoutcome measures were descriptions of study feasibility (recruitment and retention rates). We also collected informationon activity patterns (ActiGraph GT3X+ accelerometers) and health-related outcomes such as body composition (heightand weight using standard techniques), blood pressure (automatic blood pressure monitor), and psychosocial variables(questionnaires).Results: We advertised in local community newspapers to recruit participants. Over 3 weeks, 82 participants telephoned;© 2015 Ashe et al.; licensee BioMed Central. This is an Open Access article distributed under the terms of the CreativeCommons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, andreproduction in any medium, provided the original work is properly credited. The Creative Commons Public DomainDedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article,unless otherwise stated.enAshe et al. Pilot and Feasibility Studies 2015, 1:4 Page 2 of 12http://www.pilotfeasibilitystudies.com/content/1/1/4demonstrated a significant reduction in body size formiddle-aged Canadian men and women who adopted aphysician-initiated behavioral change intervention. However,results in women were not sustained at 1-year follow-up[20]. Further, in a Diabetes Prevention Program study, menwere more likely to meet physical activity goals comparedby sitting less) has the potential to support self-efficacy(mastery) [33,34] and provides a foundation to graduallyadd more daily physical activity—a “sit less to move more”approach. The novelty of this approach is that itacknowledges the physiological distinction of sedentarybehavior (too much sitting) [7] and physical inactivity(Continued from previous page)Trial registration: ClinicalTrials.gov identifier: NCT01842061Keywords: Sedentary lifestyle, Motor activity, Self-managemBackgroundThe World Health Organization ranked physical inactivityas the world’s fourth most important risk factor formortality [1], in part, because we engineered activityout of our everyday lives [2]. While there is abundantevidence that physical activity prevents chronic disease [3],many older adults fail to meet guideline recommendations[4-6]. Even those who meet guideline physical activityrecommendations spend most of the day sitting [7,8]such that sedentariness is emerging as an independentrisk factor for morbidity [9] and mortality [10].Women, in particular, are affected by higher rates ofsedentary behavior [11] which places them at increasedrisk of developing some chronic diseases [12]. In Canada,about half of women aged 45–64 years engage in leisure-time physical activity, lower than the levels of men for thesame age range [12]. Further, among women aged 60–69years, 65% had a waist circumference considered highrisk and a third of these women were obese [13].When their physical activity was measured objectively(using accelerometry), they had only 12 min/day ofmoderate to vigorous physical activity (MVPA) andspent 10 h of the waking day sitting [13]. Fewer than 5%of these women received “excellent” or “very good” fortheir fitness test. Given the physical inactivity, sedentarybehavior, obesity, and the challenge of maintaining healthybehaviors, it is of little surprise that compared with men,women are at an elevated risk for developing somechronic diseases and live with more disability in later life[14-16]. Previous studies with older women highlightedthat timing is a key factor for the uptake of healthy behaviors[17], and retirement may be an opportune time to focus ontheir own health to reduce the risk for chronic disease inlater life [18].In their systematic review, Hobbs and colleagues [19]highlight successful models for physical activity, yet theyconcluded that these results do not extend beyond 1 year.Further, they do not discuss response to these interventionsseparately for men and women. Ross and colleagues [20]with women [21].Our goal is to develop sustainable physical activitymodels that encourage people to be more active in wayst, Retirement, Womenthat are integrated into their lifestyle [22]. We hypothesizethat simple strategies, such as including more activities ofdaily living (e.g., household tasks, gardening) and/or dailypublic transit use [23], encourage movement with thedownstream benefits of more physical activity such asincreased fitness and enhanced social engagement andquality of life [24]. These more routine ways to createpositive physical activity habits [22] may, in the long run,be easier to maintain in daily life. We further hypothesizedthat an intervention based on everyday activities, deliveredin a group setting, may be positive for women at retirement.Thus, studies are needed to evaluate the potential forinactive middle-age women to become physically active as ameans to socialize and enhance health [25].Despite elevated attention paid to (and risk for) increasedsitting time in middle-aged and older adults, thereare relatively few sedentary behavior interventionsthat specifically target this age group. Gardiner andcolleagues tested feasibility of a brief goal-setting strategy toreduce sitting time in adults 60+ years [26] and noted a3.2% reduction in sitting over 2 weeks. Fitzsimons andcolleagues also tested the feasibility of a brief individualizedintervention that resulted in a 24 min/day reduction insitting [27]. Prince and colleagues [28], in their systematicreview of interventions (with a physical activity and/orsedentary behavior focus) to reduce sitting time in adults,noted that only two physical activity studies that targetedolder adults had a positive effect on sedentary behavior[29,30]. Further, of the sedentary behavior studies and/orsedentary behavior + physical activity studies, only onestudy specifically focused on older adults [31]. They used aquasi-experimental 8-week multi-prong intervention andachieved a significant reduction in sitting time [31].The Everyday Activity Supports You (EASY) model,grounded in the social-ecological model [32] and guidedby the social cognitive theory [33], aims to encouragesustainable adoption of more activity, by first reducingsitting time and then incrementally increasing physicalactivity. The success of simple strategies (such as beginning[35], but seeks to utilize behavior change techniques(BCTs), such as graded tasks (small incremental changesin daily routine) [36], for long-term habit formation. Thus,on physical activity, sedentary behavior, and health-relatedfocus that generated participant collaboration and reflexivityAshe et al. Pilot and Feasibility Studies 2015, 1:4 Page 3 of 12http://www.pilotfeasibilitystudies.com/content/1/1/4known to optimize the accessibility, uptake, effectiveness,and, in future, scale up of effective, sustainable programs tothe wider community [38].Trial design and settingThis was a phase II [39] parallel 1:1 RCT pilot of theEASY model lifestyle program (ClinicalTrials.gov identi-fier: NCT01842061). The intervention was 6 months induration, and there were three data collection periods:baseline (May 2013), midpoint (August 2013), and finalassessment (December 2013); data were analyzed inFebruary 2014. The study took place in Vancouver, BritishColumbia. Metro Vancouver (census metropolitan area)has a population of approximately 2.3 million residents[40], with 13.5% of the population 65+ years [41]. Weworked with a local community centre, within Vancouver,and originally targeted our recruitment strategies to thatoutcomes. Knowledge of this information sets the founda-tion for future effectiveness studies and scale up and spreadof the intervention.MethodsThe social ecological model [32] identifies the impact ofmultiple levels of societal influence that span individualto policy and their influence on health outcomes, healthpromotion, and behavior change. In this study, we aimedto develop a program that addressed the intersection ofmacroscale and microscale “levels” that alone and togetherinfluence the health of individuals and populations, withparticular regard to person, people (social environment),and places (community/built environment). The values ofparticipatory action research [37], especially componentsthat relate to social learning, collective problem solving,capacity building, and empowerment (self-efficacy), verynicely complement the elements of the social ecologicalmodel. We included in the EASY model a participatorywe hypothesized that the process of increasing physicalactivity begins with sitting less.The EASY model aims to extend previous workand specifically targets reduced sitting time, to initiallyincrease physical activity; to our knowledge, this approachhas not been studied in women at retirement age.Our primary objective for this phase was to test studyfeasibility by measuring participant recruitment andretention rates. Second, we sought information on partici-pants’ satisfaction with the program. Finally, we aimed todetermine the timing and resource requirements for pro-gram delivery and outcome assessments. The secondaryhealth objectives were to determine the effect of the modelneighborhood. However, the local newspaper was accessibleto residents from all regions of Vancouver.ParticipantsWe included healthy community-dwelling women 55–70years of age who self-identified as not engaging (in theprevious 3 months) in strength training or more than 30min of brisk walking or moderate exercise/week [42,43]and were able to climb a flight of stairs and walk 400 m[44]. We excluded participants who received treatment forany medical conditions that precluded walking regularly.This study was approved by the University of BritishColumbia and the Vancouver Coastal Health Research In-stitute IRB. All participants provided the following: (1)written informed consent to participate, and (2) ifthey answered yes to any question to the Physical ActivityReadiness Questionnaire Plus (PAR-Q+ [45]) duringin-person screening by the exercise physiologist, theywere required to obtain written permission from theirfamily physician to participate.RecruitmentIn May 2013, we placed advertisements in four communitynewspapers and sent emails to relevant groups (e.g., healthprofessional associations) and placed posters in the localneighborhood library and community center.Baseline assessmentWe completed all baseline assessments over a 9-dayperiod from May 21–30, 2013. Participants underwenta 60–75-min in-person assessment (including thescreen by the exercise physiologist) and took home apackage containing questionnaires and an accelerometer(ActiGraph GT3X+, ActiGraph LLC, Pensacola, FL).RandomizationAn independent statistical consultant set up the web-basedrandomization process to assign eligible participants tointervention or control groups by remote allocation, usingpermuted blocks of sizes 2 and 4. No one directly involvedin the project had access to allocation codes. As this was apilot study, no stratification was used. After all baselineassessments were completed, the study coordinatorentered participant identification numbers into the webservice to allocate groups. All interactions with the webservice were automatically logged and included informa-tion on study identification number, group allocation, andrandomization date/time.Protection against biasTreatment allocation was concealed as describedabove. Only those who did not deliver the intervention(measurement team) were blinded to group allocation.Intervention groupThe EASY model is focused on reduced sitting time toencourage more physical activity. It has three mainelements: group-based education and social support,individualized physical activity prescription (which wenamed Activity 4-1-1), and use of an activity monitor[Fitbit One (Fitbit Inc., San Francisco, CA)]. The Fitbit isan accelerometer that provides immediate feedback onactivities including daily step counts, distance walked, andstairs climbed. It also provides an online tool to monitorother behaviors (sleep and nutrition) and facilitate socialnetworking and/or friendly competitions. Participantswere not required to share Fitbit data with the researchteam. However, the exercise professionals (personal traineror exercise physiologist) used recorded step counts(from the Fitbit) to calculate step increases at individualizedsessions. Figure 1 and Additional file 1: Table S1 provide asummary of the BCTs utilized in the EASY model.Additional file 1: Figures S1 and S2 are examples ofhandouts used and generated during the group-basedsessions.There were two main phases: (1) a ramp up (consistingprofessionals. During these sessions, participants hada 10–15-min individual meeting with the exercise profes-sional for a physical activity prescription. Concurrently,the study coordinator ran group discussions with theremaining participants on topics such as dealing withsetbacks, barriers to being active, etc. The informationgenerated from the group discussions was typed andprovided to the participants the following week (please seeAdditional file 1: Figures S1 and S2 and Table S1). At twotime points over the 6 months (months 1 and 4), interven-tion participants were given a booklet of 10 transit ticketsto encourage use of public transportation.1. Ramp up: The goals of this phase were to becomefamiliar with the Fitbit, set activity goals, and developstrategies to reduce sedentary behavior. The study coord-inator led the sessions with support from two exerciseprofessionals who were in attendance at every session.This phase focused on reminding participants to reducetheir sitting time and then gradually begin introducingAshe et al. Pilot and Feasibility Studies 2015, 1:4 Page 4 of 12http://www.pilotfeasibilitystudies.com/content/1/1/4of four weekly sessions) and (2) an activation phase(consisting of five monthly sessions). During bothphases, the first hour of each session was a participatorycomponent on selected physical activity-related topics. Inthe second hour of each session, there were Activity 4-1-1sessions and concurrent brainstorming group sessions.The Activity 4-1-1 was the individual time that studyparticipants had with an exercise professional to discusstheir progress to date, goals, and individual walking(step count) prescription. We called the individualtime spent with the exercise professions as Activity 4-1-1because it was the opportunity that study participantscould seek activity “information” from the exerciseFigure 1 An overview of the behavior change techniques (BCTs). Theand underpins the three main components of the Everyday Activity Suppomore activity into daily routines. In addition, the followinginformation was provided: practical information oncommon stretches and opportunities to practice themwhile the personal trainer checked posture and a sessionfrom a pedorthist on choosing appropriate footwear forphysical activity.In the Activity 4-1-1 (individual) sessions, participantswere encouraged (if able) to increase their step countsby 5% at each visit, based initially on their first week’sstep counts from the research accelerometer data and insubsequent sessions based on their Fitbit step counts.Participants were not asked to aim for a target daily stepcount (e.g., 10,000 steps/day). Rather, it was discussedBCTs were based on the Taxonomy by Abraham and Michie [36,46],rts You (EASY) model.education sessions. Three education topics were similar torecruitment and retention rates. Second, we soughtAshe et al. Pilot and Feasibility Studies 2015, 1:4 Page 5 of 12http://www.pilotfeasibilitystudies.com/content/1/1/4information on participants’ satisfaction with the program.Finally, we aimed to determine appropriateness ofprogram delivery, resources required, and the specificcomponents of the outcomes assessment to evaluatethe EASY model in a larger trial. We defined successfor recruitment for this feasibility study as enrollingup to 15 but no less than eight participants/groupwithin the short timeframe (3 weeks); this permittedrunning two parallel arms of the study. We acknowledgethat enrolling 15 participants/group would not constitutesuccessful recruitment in a larger trial. However, thesetargets aim to provide us an estimate of interest inour program. We defined success for participant retentionas 80% of study participants completing the finalassessment. We also asked participants to rate theirsatisfaction with the program (scored out of a possiblethe intervention group (how to take public transportation,bone health and falls prevention, and personal safety), butthey did not receive information on the importance ofexercise or how to sustain an active lifestyle. Controlgroup participants had no interactions with the exerciseprofessionals nor did they receive Fitbit monitors. Controlparticipants received a $20 gift certificate at two timepoints (consistent with the delivery of the transit tickets tothe intervention group). Based on feedback from controlparticipants, the EASY model activity components (Fitbitand Activity 4-1-1) were offered to this group at the endof the study (after the final assessment).Primary outcome measuresThe main objective of this pilot study was to determinethat there were common targets (e.g., 7,000 steps/day[47]), but highlighted that each person responds differentlyto increasing physical activity.2. Activation: For this phase, one monthly class wasoffered to the intervention group. The education topicsincluded the following: (1) how to take public transporta-tion; (2) the importance of exercise; (3) bone health andfalls prevention; (4) a dietician-guided tour of a grocerystore; (5) gearing up for physical activity tips, tricks, andsafety; and (6) the final session on how to sustain activitypatterns. Our aim for the grocery store tour was twofold toprovide an opportunity for community-engagement toencourage physical activity to local destinations andprovide a general overview of a grocery store layout(with an emphasis on nutrition-rich food).Control groupWe provided control participants with separate monthly10 points, where 1 was not satisfied and 10 was highlysatisfied).Health outcome measuresAs a secondary aim, we collected health outcomemeasures at three times during the study to determinefeasibility of our assessment protocol and a preliminaryestimate of treatment effect.Activity patternsWe assessed physical activity (average daily step count)using ActiGraph GTX3+ (LLC, Fort Walton Beach, FL,USA) tri-axial accelerometers worn at the hip duringwaking hours for 7 days at each time point; Fitbits wereonly for participants’ daily use.We collected the following outcomes: MVPA (min/day)and sedentary behavior (min/day and percentage/day). Wedefined sedentary behavior as “any waking behaviorcharacterized by an energy expenditure ≤1.5 METswhile in a sitting or reclining posture” [35]. We standard-ized it by reporting percentage of sedentary time or byincluding both sedentary time (min) and total weartime (min) in the models.Accelerometry assumptions and data handlingWe reintegrated raw data (collected at 30 Hz) to 60-sepochs; we considered more than 90 min of continuouszeroes as non-wear time. To be included in the analysis,accelerometry data had to include three or more valid days(8 h/day) of wear time. Based on our systematic review[48], we used the following cut points: ≤99 counts/min assedentary time [49], 100–1,951 counts/min as lightphysical activity, and ≥1,952 counts/min for MVPA[50]. We used ActiLife (Version 6.10.0) to clean andanalyze accelerometry data.Social connectedness, self-rated health, self-efficacy, andintentions for physical activityWe used the modified Medical Outcomes Study SocialSupport Survey Instrument [51] to assess the effect ofthe intervention on participants’ social network. Weassessed self-rated health with the visual analogue scale(out of 100 points) [52]. We recorded participants’beliefs around physical activity with the McAuley ExerciseSelf-efficacy Scale [53], and we used the BehavioralIntentions for Physical Activity questionnaire [54] toassess participants’ physical activity goals.Body composition/blood pressureWe measured height (cm) and weight (kg; ConairCorporation, Glendale, AZ) using standard methods(average of two measurements) and calculated BMI asweight (kg)/height (m)2. We used BpTRU BPM-200(BpTRU Medical Devices, Coquitlam, BC) automaticcuff was used to obtain blood pressure (mmHg) instudy participants at baseline and final assessments(average of two trials).Ashe et al. Pilot and Feasibility Studies 2015, 1:4 Page 6 of 12http://www.pilotfeasibilitystudies.com/content/1/1/4Descriptive informationWe collected the following data: year of birth, highestlevel of education, and the Functional ComorbidityIndex [55].Adverse events monitoringWe requested that study participants notify the studycoordinator of any adverse events throughout the courseof the study. All adverse events were recorded by thestudy coordinator, and if deemed a serious adverseevent (SAE), a physician not involved in the studywas appointed to review them.Statistical analysisWe did not conduct a formal sample size calculationfor this feasibility study; rather, we aimed to recruitsufficient participants to generate estimates of variabilityfor our outcome measures and to generate a preliminaryestimate of effect for the intervention.We described participant characteristics using meanand standard deviations or medians and interquartilerange if appropriate. To address feasibility, we calculatedrecruitment and retention rates and report percentage;we also report participants’ program satisfaction as mean(standard deviation). For the health outcome variables,there were two sets of analyses. First, we estimatedaverage change by fitting separate linear regressionmodels for each of the health outcome variables usinggroup allocation as the only independent variable. Weperformed a second set of analyses, with constructedmodels that included baseline values as covariates [56].We report the regression coefficients and P values forthe group allocation variable and R2 values from theregression analyses to provide an estimate of model fit.Due to skewed residuals, we used log-(Y)-transformedvalues for all significance tests and regression analyses forphysical activity (step counts and MVPA). The P valuesand model R2 values for MVPA and step counts wereobtained from analyses of log-transformed data. Thebeta coefficients, however, were obtained from analyses oforiginal data to allow for interpretation of treatmenteffects as the arithmetic mean of the differences in MVPAand step counts between the two study groups. Further,we estimated confidence intervals (CIs) and standarderrors of intervention effects for these variables (stepcounts and MVPA) through nonparametric bootstrappingusing 1,000 resamples with random seed set to a value of1,234. We used Stata version 12 (StataCorp, CollegeStation, TX, USA).ResultsThis study ran from May to December 2013 inclusiveof recruitment and final assessment. We were able toutilize all outcome measurement instruments initiallyproposed, including the request for study partici-pants to wear an accelerometer for 7 days followingassessment.Eighty two participants responded to newspaper ads,56 participants were eligible following telephone screenby a trained research assistant and 26 participants agreedto take part in the study. Of the study participants whowere not eligible to enroll in the study, the three reasonsgiven were: as follows already engaging in an exerciseprogram (N = 19), <55 years old (N = 5), and >70 yearsold (N = 2). Of 56 eligible participants, 30 declined toenroll. Work demands were cited as the main reason forbeing unavailable to attend sessions. One participant,who was referred back to her family physician followingscreening, due to an existing health condition, did notreceive physician approval to take part in the study. SeeFigure 2 for the CONSORT 2010 flow diagram.Participants had mean (SD) age of 64.1 (4.6) years andmedian (IQR) of 2 (3) comorbidities. All participants com-pleted secondary school, and some had further education(Table 1). Two intervention participants (2/12, 17%) andfour control participants were working (4/8, 50%).Following baseline assessment, 20 participants wererequired to return to their family physician to obtainwritten permission. There were 25/56 (45%) participantswho were randomized by remote web service resultingin 13 participants in the intervention group and 12participants in the control group. At 6 months, 20/25(80%) of study participants completed the final assess-ment, including 12/13 (92%) intervention and 8/12 (67%)control participants (Figure 2). During the course of thestudy, one intervention and one control participant eachsustained an SAE that were deemed unrelated to studyparticipation; however, the control participant’s injuryprevented her from wearing the accelerometer at thefinal assessment.For intervention group sessions, attendance rangedfrom n = 6 (46%) to n = 13 (100%); median (IQR) was10 (3.8) participants/session. Control sessions had lowerattendance at education sessions [median (IQR) 6.5 (1.8)participants]. Overall, at 6 months, participants in theintervention group rated their satisfaction with theprogram as [mean (SD)] 9 (1) points; it was 9 (1) pointsfor control group participants.We provide initial estimates of treatment effect forthe EASY model; however, these early results may notbe replicated in a larger, definitive trial. At the 3- and6-month time point intervention, participants increasedtheir daily step counts and MVPA and decreased sed-entary time; there was a larger increase at midpoint(August) compared with final assessment (November).Control participants decreased both step counts andMVPA over the 6-month time period; they also increasedsitting time. There was a statistically significant between-Ashe et al. Pilot and Feasibility Studies 2015, 1:4 Page 7 of 12http://www.pilotfeasibilitystudies.com/content/1/1/4group difference for step count 2,080 [95% CI 704, 4,918]at the final assessment in both the unadjusted (P = 0.046)and adjusted models (P = 0.040) favoring EASY. Therewere no statistically significant differences between groupsfor MVPA or sedentary time (Tables 2 and 3).Table 4 presents results for the between-groupanalyses of health-related outcomes. There was anaverage between-group difference of −4.3 [95% CI−6.22, −2.40] kg and reduction in diastolic bloodpressure of −8.54 [95% CI −16.89, −0.198] mmHg, infavor of EASY. There were no significant differencesbetween groups for any other variables except unadjustedbehavioral intentions, where there was a 0.82 [0.07, 1.56]difference favoring EASY.DiscussionTo our knowledge, the EASY model is the first interven-tion in middle-aged women to specifically target reducedsitting time as a catalyst for engaging in more physicalactivity. We demonstrated interest in our study andrecruited an adequate number of participants to pilotthe intervention. We also showed that we could deliverFigure 2 CONSORT 2010 Flow diagram for the EASY-Pilot study.the EASY intervention as planned and the appropriatenessof outcome measurements. Specifically, participants inboth groups had a high level of satisfaction with theprogram, and we retained 92% of intervention groupparticipants at 6 months. However, we note that for alarger trial, we will need to provide more time for recruit-ment and/or different strategies to meet recruitment goals.The study also supports the feasibility of using anovel activity monitor (the Fitbit) and online resources, tosupport women to be more active in their daily routine.The program was designed to instill confidence andknowledge about key elements of a sustainable physicalactivity program and to support people to make their ownchoices regarding an active lifestyle—rather than prescrib-ing a specific one-size-fits-all program. One of the studyparticipants expressed that the EASY model was “not justanother walking program”—it was an opportunity forthem to acquire skills and resources to manage their ownphysical activity.In this study, sufficient participants were recruitedin the timeframe to complete the pilot as planned.Although 30 participants declined participation, 21 statedTable 1 Characteristics of study participants across the three time points of the studyBaseline Midpoint, 3 months Final, 6 monthsControl Intervention Control Intervention Control InterventionN = 8 N = 12 N = 8 N = 12 N = 8 N = 12Age (years) mean (SD) 63.1 (4.8) 64.8 (4.6)BMI 32.9 (6.8) 26.9 (6.8)Education: secondary education+ 8 12Employment: working 4 2Weight (kg)Mean (SD) 90.19 (18.94) 69.69 (19.32) 90.06 (18.50) 67.93 (18.55) 91.6 (19.04) 67.33 (18.57)Systolic blood pressure (mmHg)Mean (SD) 139.94 (13.33) 127.92 (16.31) – – 138.56 (14.55) 117.04 (18.73)Ashe et al. Pilot and Feasibility Studies 2015, 1:4 Page 8 of 12http://www.pilotfeasibilitystudies.com/content/1/1/4Diastolic blood pressure (mmHg)Mean (SD) 83.44 (9.31) 77.29 (6.85)Behavior intentions/5Median (IQR) 3.6 (1.1) 4.4 (1.5)Exercise self-efficacy/10Median (IQR) 7.08 (1.75) 7.75 (2.17)Self-rated health/100Mean (SD) 86.63 (17.52) 79.42 (14.23)Social support/100Mean (SD) 86.11 (8.42) 79.04 (16.24)it was because they were still working and unable to at-tend due to timing of the sessions. This was consideredprior to the study; however, it was not possible to accom-modate multiple sessions for the pilot study. The fullprotocol will provide sessions across a variety of days andtimes. Nonetheless, recruiting via local newspapers wassuccessful here, and this mode and other recruitmenttechniques [57] will be employed for the future study.Another viable option for the next phase is to workwith larger organizations to deliver the EASY modelas a workplace intervention as part of a retirementTable 2 Physical activity and sedentary behavior outcomes foBaselineControl Intervention C(N = 7) (N = 12) (Step count (steps/day)Mean (SD) 5,340 (1,966) 6,402 (2,534) 4,2Median (IQR) 4,786 (4,313) 5,918 (4,599) 4,0MVPA (min/day)Mean (SD) 24.33 (32.69) 23.39 (15.21) 12Median (IQR) 11.33 (27.57) 19.07 (24.5) 7.4Sedentary behavior (%)Mean (SD) 62.42 (12.95) 67.75 (7.45) 70MVPA: moderate to vigorous physical activity.BMI: body mass index; IQR: interquartile range; SD: standard deviation.– – 83.38 (8.93) 70.88 (9.57)3.3 (1.3) 4.0 (1.3) 3.1 (1.3) 4.0 (0.70)5.17 (1.92) 8.08 (1.92) 6.83 (3.33) 8.25 (1.5)86.5 (14.0) 79.83 (19.19) 77.5 (22.68) 83.75 (16.50)86.45 (8.99) 78.56 (13.82) 88.13 (5.60) 79.39 (11.80)package initiative, and in this way, it would be possibleto utilize a known sampling frame to address widergeneralizability of our findings.Study participants had a high level of engagement withtheir attendance, and both groups rated their satisfactionwith the program as 9/10. Reasons to explain thisinclude living in a walkable city, the Fitbit monitor,financial incentives, and frequent contact. However,equally noticeable was the lower rate of retention forthe control participants. Three participants droppedout before the study began because of group allocation;r the study groups at three time pointsMidpoint, 3 months Final, 6 monthsontrol Intervention Control InterventionN = 7) (N = 12) (N = 7) (N = 12)51 (1,185) 8,038 (3,317) 4,593 (663) 7,606 (3,917)02 (1,925) 6,914 (5,936) 4,444 (988) 6,295 (5,255).22 (9.50) 34.31 (24.32) 13.49 (8.03) 33.06 (28.83)3 (13.57) 34.36 (28.79) 10.00 (18.00) 27.36 (34.36).66 (4.95) 65.56 (7.20) 67.23 (4.68) 66.17 (7.06)Systolic blood pressure(mmHg)P value 0.014 0.069Model R2 0.294 0.474β coefficient [95% CI] −21.52 [−38.04, −5.00] −14.64 [−30.55, 1.26]Diastolic blood pressure(mmHg)P value 0.009 0.045Model R2 0.324 0.525β coefficient [95% CI] −12.5 [−21.44,-3.56] −8.54 [−16.89, −0.198]Behavioral intentions forphysical activityP value 0.033 0.118Model R2 0.228 0.577β coefficient [95% CI] 0.817 [0.07, 1.56] 0.469 [−0.13, 1.07]Ashe et al. Pilot and Feasibility Studies 2015, 1:4 Page 9 of 12http://www.pilotfeasibilitystudies.com/content/1/1/4Table 3 Average difference between groups for physicalactivity measures at final assessmentUnadjusted Adjusted for baselineStep counts (steps/day)P valuea 0.046 0.040Model R2a 0.214 0.678β coefficient 3,012 2,080[95% CI]b [1,257, 5,743] [704, 4,918]MVPA (min/day)P valuea 0.088 0.150Model R2a 0.162 0.555β coefficient 19.57 19.96[95% CI] b [6.18, 41.43] [5.67, 62.00]Sedentary behavior (min/day)P value 0.673 0.489Model R2 0.595 0.665β coefficient −12.41 −21.14[95% CI] [−73.68, 48.85] [−84.89, 42.60]MVPA: moderate to vigorous physical activity; aP values and model R2 forMVPA and step counts were obtained from log-transformed data; b95% CIswere estimated from original data using nonparametric bootstrapping with1,000 resamples and random seed set to 1,234; all other values were obtainedfrom original data.but notably, eight of the nine control participantscompleted the final assessment. The control partici-pants who remained in the study had a high level ofsatisfaction, which may reflect group interactions withother study participants and/or program organizationand delivery. Attrition rates for lifestyle interventionsvary; in a Cochrane Review of lifestyle interventionsfor adults with diabetes, attrition rates ranged from0–30% [58]. The results from the present study sug-gest that an RCT design for a larger trial, based onthe current protocol, could introduce a potential lossto follow-up in the control group. Given the enthusiasmfor the intervention and the readiness for change by studyparticipants, a stepped wedge protocol [59] may enhancethe study design.Our secondary objectives were to assess the effect ofthe intervention on study participants’ physical activityand health outcomes. We note differences in step countsbetween groups at final assessment but observed thatthe groups were slightly different at baseline. Thisshould be considered when interpreting the resultsand in the design of the future study (e.g., stratifyparticipants by step counts above or below a cutpoint). An unanticipated finding in this study was a4-kg weight loss, on average, favoring the interventiongroup, although we recognized that there were somedifferences in weight between groups at study commence-ment that may have had an effect on our results. FranzTable 4 Average difference between groups at finalassessment for health outcomes and other self-reportedmeasuresUnadjusted Adjusted forbaselineWeight (kg)P value 0.011 <0.001Model R2 0.309 0.994β coefficient [95% CI] −24.28 [−42.23, −6.29] −4.31 [−6.22, −2.40]and colleagues [60] conducted a systematic review andmeta-analyses of exercise-only interventions for weightloss. Minimal average weight loss at 12 months [1.9 (3.6)kg] in the exercise group was no better than advice alone.Thus, there is a clear role for dietary considerations in anystudy that aims to positively influence body weight.Although we provided one educational session on nutritionduring a tour of a local grocery store with a dietitian andmodelled healthy food choices with the lunches provided,dietary behaviors and body weight were not thefocus of the study. Another possible explanation isthat reductions in sitting time with increases inExercise self-efficacyP value 0.128 0.167Model R2 0.124 0.215β coefficient [95% CI] 1.21 [−0.379,2.80] 1.07 [−0.49,2.64]Self-rated healthP value 0.484 0.069Model R2 0.028 0.523β coefficient [95% CI] 6.25 [−12.10, 24.60] 12.56 [−1.10, 26.22]Social supportP value 0.068 0.150Model R2 0.173 0.564β coefficient [95% CI] −8.74 [−18.20, 0.718] −5.25 [−12.59, 2.10]Ashe et al. Pilot and Feasibility Studies 2015, 1:4 Page 10 of 12http://www.pilotfeasibilitystudies.com/content/1/1/4physical activity were “gateway behaviors” for changes indiet [61]. While Fleig and colleagues [62] noted thatpositive changes in physical activity occurred in parallel tonutritional changes, there are other interventionswhich did not note this synergy [63,64]. Explorationof factors that contributed to change in body compositionassociated with our model would be an important focusfor future studies.Our study has limitations. First, the sample size waspurposely small to assess key features such as participantrecruitment and retention to guide the development andplanning of the next phase of this research (e.g., interestin the study, feasibility of delivering the intervention,estimating a sample size for the larger study). Althoughour current strategies were successful in enrolling partic-ipants in a short time period, a recruitment strategy thatincluded a known sampling frame (such as with aworkplace intervention) would provide additional in-formation to guide future studies. Second, the differencein outcomes between groups reported at 6 months arepreliminary evidence that could be used to inform a largertrial, but these results may not be present in a scaled upversion of the intervention. Third, the observed differ-ences are likely conservative because of the lower num-ber of control participants who completed the finalassessment. In the larger trial, more sophisticatedmethods (including multiple imputations) will be usedto address any missing data [65]. Finally, the EASYmodel adopts a multipronged approach; thus, it is dif-ficult to discern the relative contribution of each elementto any changes observed. Olander and colleagues [66]observed that effective BCTs for increasing self-efficacy inactivity trials included action planning, time management,self-management of behavior, and social influences—components of which are contained within EASY.However, we observed a difference for the unadjustedmeasure of behavior intentions only but did not notea between group difference for self-efficacy measures.The area of determining which BCT was effective willbe the focus of future studies that will be designedbased on the findings herein.ConclusionsIn conclusion, the EASY model was feasible to deliver ina community setting to women at retirement age. Partici-pants were highly engaged in, and satisfied with, the EASYmodel, and 92% of intervention participants completed thefinal assessment at 6 months. It is promising that, despiteour sample size, the intervention was an effective means toincrease physical activity and decrease weight and bloodpressure in this retirement age cohort. A phase III trial,using a different study design, is needed to ascertainthe effectiveness of scaling up and long-term sustainabilityof the EASY model.Additional fileAdditional file 1: Includes a participant handout and a summary ofthe EASY behavioral change techniques (BCTs). Additional file 1:Figure S1 was a handout given to participants to review their currentbehavior and create a plan for their future activity patterns. Additional file 1:Table S1 explains in detail the BCTs employed with the EASY model.Competing interestsThe authors declare that they have no competing interests.Authors’ contributionsMCA was responsible for the overall project and was involved in the studyconception and design, analysis, and interpretation of data. HM and MWwere involved in study concept and design; MM and GW were involved indata acquisition; JP and JS were involved in study design and data analysis;and MW, CH, MD, PG, LG, KM, MM, JP, JS, JSG, and HM were involved in theinterpretation of data. All authors read, revised critically for importantintellectual content, and approved the final manuscript.AcknowledgementsWe gratefully acknowledge the generosity of our study participants and thesupport of the Centre for Hip Health and Mobility staff, Ms. Kate Milne andMs. Julie Iverson. We also acknowledge Canadian Institutes of HealthResearch (CIHR) for operation funds for this project (funding referencenumber AAM-108607). We acknowledge career award support forDr. Ashe and Dr. Sims-Gould from CIHR (New Investigator Award) and theMichael Smith Foundation for Health Research (MSFHR) Scholar Award.Dr. Hoppmann is supported by career awards from MSFHR and the CanadaResearch Chairs Program. Dr. Gardiner is supported by an Australian NationalHealth and Medical Research Council Centre of Research Excellence(Grant No. 1000986). Dr. Giangregorio is the recipient of a CIHR NewInvestigator Award and an Early Researcher Award from the Ontario Ministryof Research and Innovation. The sponsor had no role in the study design;collection, analysis, and interpretation of data; writing the report; and thedecision to submit the report for publication.Author details1Centre for Hip Health and Mobility, 7F-2635 Laurel Street, Vancouver, BCV5Z 1 M9, Canada. 2Department of Family Practice, University of BritishColumbia (UBC), 320-5950 University Boulevard, Vancouver, BC V6T 1Z3,Canada. 3Faculty of Health Sciences, Simon Fraser University, Blusson Hall Rm11522, 8888 University Drive, Burnaby, BC V5A 1S6, Canada. 4UBCDepartment of Psychology, 2136 West Mall, Vancouver, BC V6T 1Z4, Canada.5School of Public Health, The University of Queensland, Level 3, Public HealthBuilding, Herston Rd, Herston, Queensland 4006, Australia. 6TranslatingResearch Into Practice (TRIP) Centre, Mater Research Institute-The Universityof Queensland, Level 3 Aubigny Place, Raymond Terrace, South Brisbane,Queensland 4101, Australia. 7Department of Kinesiology, University ofWaterloo, 200 University Ave W, Waterloo, Ontario N1H 8 K4, Canada. 8UBCDepartment of Medicine, Division of Geriatric Medicine, Room 7185, 2775Laurel Street, Vancouver, BC N2L 3G1, Canada. 9UBC School of Populationand Public Health, 2206 East Mall, Vancouver, BC V6T 1Z3, Canada. 10Centrefor Health Evaluation and Outcomes Sciences, 588-1081 Burrard Street, St.Paul’s Hospital, Vancouver, BC V6Z 1Y6, Canada. 11UBC Department ofOrthopaedics, 3114-910 West 10th Avenue, Vancouver, BC V5Z 1 M9, Canada.Received: 27 May 2014 Accepted: 5 November 2014Published: 12 January 2015References1. 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Whatare the most effective techniques in changing obese individuals’physical activity self-efficacy and behaviour: a systematic review andmeta-analysis. Int J Behav Nutr Phys Act. 2013; 10:29.doi:10.1186/2055-5784-1-4Cite this article as: Ashe et al.: “Not just another walking program”:Everyday Activity Supports You (EASY) model—a randomized pilotstudy for a parallel randomized controlled trial. Pilot and FeasibilityStudies 2015 1:4.Submit your manuscript at www.biomedcentral.com/submit


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