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Text4Heart II – improving medication adherence in people with heart disease: a study protocol for a randomized… Maddison, Ralph; Stewart, Ralph; Doughty, Rob; Scott, Tony; Kerr, Andrew; Benatar, Jocelyne; Whittaker, Robyn; Rawstorn, Jonathan C; Rolleston, Anna; Jiang, Yannan; Estabrooks, Paul; Sullivan, Rachel K; Bartley, Hannah; Pfaeffli Dale, Leila Jan 25, 2018

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STUDY PROTOCOL Open AccessText4Heart II – improving medicationadherence in people with heart disease: astudy protocol for a randomized controlledtrialRalph Maddison1*, Ralph Stewart2, Rob Doughty3, Tony Scott4, Andrew Kerr5, Jocelyne Benatar2, Robyn Whittaker6,Jonathan C. Rawstorn1, Anna Rolleston7, Yannan Jiang6, Paul Estabrooks8, Rachel Karen Sullivan9,Hannah Bartley6 and Leila Pfaeffli Dale10AbstractBackground: Cardiac rehabilitation (CR) is an essential component of contemporary management for patients withcoronary heart disease, including following an acute coronary syndrome (ACS). CR typically involves education andsupport to assist people following an ACS to make lifestyle changes and prevent subsequent events. Despite itsbenefits, uptake and participation in tradition CR programs is low. The use of mobile technologies (mHealth) offersthe potential to improve reach, access, and delivery of CR support. We aim to determine the effectiveness andcost-effectiveness of a text-messaging intervention (Text4Heart II) to improve adherence to medication and lifestylechange in addition to usual care in people following an ACS. A second aim is to use the RE-AIM framework toinform the potential implementation of Text4Heart II within health services in New Zealand.Methods: Text4Heart II is a two-arm, parallel, superiority randomized controlled trial conducted in two largemetropolitan hospitals in Auckland, New Zealand. Three hundred and thirty participants will be randomized toeither a 24-week theory- and evidence-based personalized text message program to support self-management inaddition to usual CR, or usual CR alone (control). Outcomes are assessed at 6 and 12 months. The primary outcomeis the proportion of participants adhering to medication at 6 months as measured by dispensed records. Secondaryoutcomes include medication adherence at 12 months, the proportion of participants adhering to self-reportedhealthy behaviors (physical activity, fruit and vegetable consumption, moderating alcohol intake and smoking status)measured using a composite health behavior score, self-reported medication adherence, cardiovascular risk factors(lipids, blood pressure), readmissions and related hospital events at 6 and 12 months. A cost-effectiveness analysis willalso be conducted. Using the RE-AIM framework, we will determine uptake and sustainability of the intervention.Discussion: The Text4Heart II trial will determine the effectiveness of a text-messaging intervention to improveadherence to medication and lifestyle behaviors at both 6 and 12 months. Using the RE-AIM framework this trial willprovide much needed data and insight into the potential implementation of Text4Heart II. This trial addresses manylimitations/criticisms of previous mHealth trials; it builds on our Text4Heart pilot trial, it is adequately powered, hassufficient duration to elicit behavior change, and the follow-up assessments (6 and 12 months) are long enough todetermine the sustained effect of the intervention.(Continued on next page)* Correspondence: ralph.maddison@deakin.edu.au1Institute for Physical Activity and Nutrition, Deakin University, Geelong, VIC,AustraliaFull list of author information is available at the end of the article© The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, andreproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link tothe Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Maddison et al. Trials  (2018) 19:70 DOI 10.1186/s13063-018-2468-z(Continued from previous page)Trial registration: Australian New Zealand Clinical Trials Registry, ID: ACTRN12616000422426. Registered retrospectivelyon 1 April 2016.Keywords: Cardiovascular disease, Self-management, Text messaging, Risk factorsBackgroundCardiovascular diseases (CVD) are the leading causes ofpremature death and disability worldwide, accountingfor 30% of all global deaths [1]. By 2030, almost 23.6million people will die from CVD, mainly coronary heartdisease (CHD), and the total number of disability-adjusted life years attributable to CVD is expected toreach approximately 204 million [1]. People with CVDare more likely to develop future cardiac events such asunstable angina, myocardial infarction (MI), and suddencardiac death [2]. This places a huge burden on health-care systems, with the US spending US$444 billion onCVD-related treatments in 2010 [3].Improved diagnosis, treatment, and management havesubstantially reduced the mortality rate of individualsliving with CHD [4, 5]; however, those who have experi-enced an MI have a 20–40% risk of a recurrent event ordeath in the next 5 years [4, 5]. Approximately 80% ofCHD is caused by modifiable risk factors including phys-ical inactivity, smoking, unhealthy diet, and harmfulalcohol consumption [6], and effective evidence-basedsecondary prevention treatments—such as implementinglifestyle changes and adhering to prescribed medicationregimens (self-management)—can aid recovery andreduce recurrent cardiac events. Improvements in lipids,systolic blood pressure, smoking prevalence, and phys-ical activity account for an estimated 47% of the totalimprovement in case fatality [5].Management of CHDAcute coronary syndrome (ACS) encompasses unstableangina, and MI. Following diagnosis of an ACS, patientsshould receive a range of evidence-based preventivetreatments that include appropriate clinical follow-up, aswell as referral to programs that provide education andsupport self-management for the secondary preventionof disease—commonly known as cardiac rehabilitation(CR). A core focus of CR is to encourage people to makehealthy lifestyle changes to reduce subsequent cardiacevents. Lifestyle behavior changes include regular phys-ical activity, eating a healthy diet, stopping smoking, re-ducing harmful alcohol intake, and taking medications asper a prescribed regimen [7]. Empowering self-managementis critical for people with an ACS to maximize treatmentbenefits [8].CR is an essential part of contemporary managementfor people with an ACS. It has been shown to reducecardiovascular deaths and hospital readmissions by 25%[7], and is cost-effective for those who participate [9]. ACochrane systematic review [10] of CR reported a statisti-cally significant reduction in cardiovascular mortality of26% (odds ratio (OR) 0.74, 95% CI 0.57 to 0.96) and areduction in all-cause mortality of 13% (OR 0.87, 95%confidence interval (CI) 0.71 to 1.05). This magnitude ofeffect is consistent with a review of cohort studies andrandomized controlled trials (RCTs) [11].Despite these benefits, CR participation is inadequatein all countries in which it has been assessed [12]. Lowlevels of patient participation and completion (14–43%after MI) have been reported in Australia, France, theUnited Kingdom, and New Zealand with high levels ofdropout after enrollment [13–17]. Lack of completionreduces the benefits of CR, such as improvements inCVD risk factors [18]. Patient-oriented, medical, andhealthcare system factors associated with suboptimalparticipation include availability, affordability and acces-sibility of a program, as well as work/domestic commit-ments and psychological barriers [19, 20]. Current CRdelivery approaches do not suit all people and newmodels are needed to improve the uptake and comple-tion of CR. A range of options should be available forpeople according to their preferences and needs [21].New approaches to enhance self-managementA recent systematic review of alternative models of carefound multifactorial individualized telehealth and com-munity- or home-based CR were effective alternatives asthey have produced similar reductions in CVD risk factorscompared with hospital-based programs [22]. This echoesfindings from other reviews of home-based CR [23] and tel-ehealth [24]. There is a paucity of research describing theeffectiveness of alternative models of CR in rural, remote,and culturally diverse populations. However, evidence sug-gests that hospital-based strategies may not be able to de-liver effective CR to these populations. Local healthcaresystems may need to integrate alternative models of CR,such as brief interventions tailored to individual’s risk factorprofiles, as well as community- or home-based programs,to ensure that choices are available that best fit patient’sneeds, risk factor profile, and preferences.The potential of mobile phone delivered self-managementWhile telehealth [24] and Internet-based programs havebeen shown to be effective, they are limited due toMaddison et al. Trials  (2018) 19:70 Page 2 of 10predominant reliance on desktop and landline communi-cation, whereas technology is now more mobile. Mobilephones are the most common device for communicationworldwide—including developing countries—and are usedto deliver behavioral-change programs and improvedisease self-management [25]. Mobile phones have poten-tial to influence behavior at a population level because thetechnology is widely available globally, inexpensive, andallows instant delivery of information [26].Text-messaging—or short message service (SMS)—isthe most widely used mobile phone intervention. Twosystematic reviews [27, 28] support the effectiveness ofSMS interventions across a range of risk behaviors (e.g.,smoking) and chronic conditions (e.g., diabetes andasthma). A 24-week text-messaging intervention in theHEART trial increased walking and leisure time exercisein people who were post ACS (n = 171), but did notincrease maximal exercise capacity [29, 30]. The TEXTME trial—which is the largest trial in people with CVD(n = 710) [31]—reported statistically significant positiveeffects on low-density lipoprotein (LDL) cholesterol, andsizeable effects on secondary outcomes such as bloodpressure and physical activity. This intervention involveddelivery of regular semi-personalized text messages pro-viding advice, motivation, and information that aimed toimprove diet, increase physical activity, and encouragesmoking cessation. While this study represents a goodinitial evaluation of a text messaging intervention for en-hancing CHD outcomes, future work is still required.First, it was conducted in a single center in Australia withmany participants excluded due to language barriers or notowning a mobile phone, which limits its generalizability.Second, the intervention was evaluated as a stand-alonestrategy, thus it was unclear whether the intervention wasmore or less beneficial to those in traditional programs.Third, implementation of the intervention in a real-worldsetting was not assessed in the study.We previously conducted the Text4Heart randomizedcontrolled pilot trial (n = 123) [32, 33], of a 6-monththeory-based program of daily text messages and a sup-porting website in addition to usual CR services. Using acomposite measure of lifestyle change (exercise, diet,smoking, alcohol), we observed a significant treatmenteffect on adherence to lifestyle behaviors at 3 months(adjusted OR = 2.55, 95% CI 1.12 to 5.84; p = .03), but notat 6 months (adjusted OR = 1.93, 95% CI 0.83 to 4.53; p= .13). At 6 months, the intervention group had greaterself-reported medication adherence (mean difference inscores: 0.58, 95% CI 0.19 to 0.97; p = .004), with 51%reporting high adherence compared to 32% in the controlcondition. Text4Heart was also associated with loweredLDL cholesterol at 6 months compared with control(mean difference: − 0.25, 95% CI -0.49 to 0.003; p = .05).Participants reported high fidelity to the text-messagecomponent of the intervention, with 85% of interventionparticipants reading all their messages. Text4Heart waswell-received with 84% of participants reporting that theprogram helped them recover, and 90% of participantswould have recommended it to others who had a cardiacevent [33]. A definitive trial of Text4Heart to determineits effectiveness using an objective measure is nowrequired to determine the sustained effect of the interven-tion for augmenting existing cardiovascular services.AimsTo determine the effectiveness and cost-effectiveness ofthe Text4Heart II self-management program—inaddition to usual care—to improve adherence to medica-tion and lifestyle change in people with an ACS. A sec-ond aim is to use the RE-AIM framework [34] to informthe potential implementation of the Text4Heart II pro-gram to augment existing CR services with two districthealth boards in Auckland, New Zealand.Hypotheses1. Text4Heart II will improve self-management of ACS,as seen by increased adherence to medication andlifestyle behaviors at 6 and 12 months compared tostandard CR care alone,2. Text4Heart II will be cost-effective, and3. Text4Heart II will be imminently scalable for rollout within the existing healthcare system in NewZealand (district health boards)MethodsThe Text4Heart II trial is a two-arm, parallel, super-iority RCT conducted in two large metropolitan hos-pitals in Auckland, New Zealand. The study protocolis in accord with the Standard Protocol Items: Rec-ommendations for Interventional Trials (SPIRIT) 2013Statement [35], and was prospectively registered inthe Australian New Zealand Clinical Trials Registryon 1 April 2016, (ACTRN12616000422426). Theintervention is described according to the Consoli-dated Standards of Reporting Trials (CONSORT)-eHealth Checklist [36]. The trial schedule is presentedin Fig. 1, and the SPIRIT Checklist is reported inAdditional file 1.Study population and recruitmentAdults who are clinically stable, able to read English,and provide informed consent are invited to participateinto the study either while inpatients, or shortly afterdischarge following ACS or post percutaneous coronaryintervention. Exclusion criteria include untreated ven-tricular tachycardia, severe heart failure, life-threateningco-existing disease with life expectancy below 1 year, andMaddison et al. Trials  (2018) 19:70 Page 3 of 10significant exercise limitations other than CVD. Potentialparticipants will be given information sheets by a re-searcher and informed consent will be obtained either inwriting, or verbally if the participant is already discharged.All patients admitted with ACS or who undergo angi-ography are registered in the All New Zealand AcuteCoronary Syndrome Quality Improvement register (AN-ZACS-QI) [37]. ANZACS-QI collects detailed informa-tion on risk factors, diagnosis, investigations, as well asmanagement and complications during admission, and isembedded in > 90% of hospitals in New Zealand. Dataare able to be linked to laboratory results and dispensingfrom chemists. Anonymized linkage to patients’ uniqueNational Health Index number allows data to be ob-tained on mortality and rehospitalization for subsequentanalysis [38]. This study design, utilizing the strengths ofthe clinical registry combined with the specific clinicaltrial protocol, provides a unique opportunity to collectstudy data at low cost and with no additional participantburden.Sample sizeA total of 330 participants (165 per group) will provide80% power at the 5% level of significance (two-sided) todetect an absolute difference of 15% between the twogroups, in the proportions of participants adherent tomedication 6 months after randomization (assuming acontrol rate of 30%). This is a conservative control rateand is based on our self-reported Text4Heart pilot data,and New Zealand research that found only 60% of pa-tients had a Medication Dispensing Ratio (SDR) > 0.8for statins only [39]. This value is likely to be lowerwhen all classes of medication (statins, antihyperten-sive, and antiplatelet therapies) are considered. If thecontrol rate was indeed 60% then a total of 304 partici-pants would be required to detect an absolute differenceof 15%; thus, we would be adequately powered with ourproposed sample size.Randomization, allocation concealment, and blindingUpon completion of baseline assessment a researcherwill randomly allocate eligible participants at a 1:1 ratioto the intervention or control arm, using blocked (vari-able block sizes, 2 or 4) stratified (hospital site)randomization. The allocation sequence will be com-puter generated by an independent statistician not in-volved with trial conduct, and concealed by a centralizedcomputer system that will reveal treatment allocationonly after submission of baseline data. Study investiga-tors (but not participants) are blinded to interventionallocation throughout the trial. The primary outcome,however, is derived from data linkage, which is blind totreatment allocation.Fig. 1 Schedule of enrollment, interventions, and assessments (Standard Protocol Items: Recommendations for Interventional Trials(SPIRIT) Figure)Maddison et al. Trials  (2018) 19:70 Page 4 of 10Intervention and controlAll participants will receive usual care, which includesCR support. In addition, those allocated to theText4Heart II intervention arm will receive a personal-ized, automated program of CR delivered via text mes-sage over 24 weeks. The overall goals of the interventionare to encourage and promote adherence to medication,healthy diet, stress management, regular exercise,reduced alcohol consumption, and smoking cessation (ifapplicable). Participants will be able choose additionalfocussed intervention modules at baseline that addressrisk factors that they identify as most relevant to them,such as physical activity, heart healthy diet, stress man-agement, and smoking cessation.Participants receive one message per day for the first12 weeks, a technical support phone call at 12 weeks,and five messages per week for the remaining 12 weeks.Messages will be personalized (including participants’names) and sent at times to suit participants. The inter-vention is predominantly unidirectional but participantswill be able to reply to text messages and a researcherwill answer within 24 h. All participants will be offeredbrief training at enrollment on how to read, delete, andsave text messages. Messages are categorized into fourgroups (see below). Non-smokers receive one to twogeneral heart health messages, one to two physical activ-ity messages, and one to two dietary messages per week.Smokers receive one general heart health message, oneto two physical activity messages, one to two dietarymessages, and one to two smoking-cessation supportmessages per week.At registration, intervention group participants willselect their preferred receipt times for educational (earlymorning, late morning, early afternoon, late afternoon,or evening) and medication reminder messages toensure that the timing is appropriate for their needs.Details of the text-message content are provided below.Intervention contentGeneral heart health and medication adherenceGeneral health information messages that include factsabout risk factors and medication will be provided. Mes-sages will include information and strategies to help par-ticipants adhere to their prescribed medicationregimen—including information on the value of takingmedication to reduce recurrent events and hospitalization,reminders to have a regular check-up with their physician,enhancing self-management, and addressing illnessperceptions and medications beliefs. In addition, advicewill be given about contacting their physician if unwell,practical tips on how to improve lifestyle though habit for-mation and environmental prompts, and how to enlistsupport from others.Physical activityParticipants will receive messages derived from thesuccessful HEART trial [29, 30], that address the import-ance of being physically active. Message content willinclude suggested activities, key strategies to enhanceuptake and maintenance of physical activity (e.g., goalsetting, self-monitoring), and a generic exercise prescrip-tion that suggests the type, frequency, duration, andintensity of exercise.Dietary behaviorParticipants will be supported to reduce dietary saturatedfat and salt intake, and to manage their weight. All contentwas developed, pre-tested and successfully piloted prior tothe Text4Heart II trial [40]. Participants will receive textmessages promoting healthy eating strategies, advice onchoosing healthy food, and food preparation. Themessages focus on supporting behavior-change strategies.Smoking cessationParticipants who smoke tobacco will receive compo-nents of the successful STOMP text-messagingsmoking-cessation intervention [41–43]. They will besent regular messages providing smoking-cessation ad-vice and support (e.g., symptoms to expect on quitting,tips to avoid weight gain and to cope with craving, ad-vice on avoiding smoking triggers).All messages are grounded in established psychological(Common Sense Model) [44] and behavior-change(Social Cognitive) theory [45] and will focus on modify-ing perceptions of the symptoms, timeline, causes, con-sequences, understanding of, personal control over, andability of treatment to prevent, CVD [46], as well asaltering the key mediators of behavior change includingself-efficacy, social support, and motivation.OutcomesAll outcomes are assessed at 6 and 12 months postrandomization. The primary outcome is the proportionof participants adhering to medication at 6 months.Medication adherence is defined as SDRs of 80% for sta-tins, antihypertensive, and antiplatelet therapy classes ofmedication (calculated separately)—consistent withguideline-recommended therapy [47]—where SDR iscalculated as the number of days that the supply is ob-tained divided by the number of days in the observationperiod. Participants’ community pharmacy dispensingrecords will be linked using their unique National HealthIndex number via the National Pharmaceuticals Collec-tion database. This approach has been used successfullyin New Zealand to assess statin use [39]. To adjust fordays not covered due to death or days spent in hospitalthese periods are subtracted from the 6-month coveragetime. The number of days supplied will be estimatedMaddison et al. Trials  (2018) 19:70 Page 5 of 10from strength per unit and daily dose variables summedfrom pharmacy claims during the observation period. Toaccount for any previous supply of the medication(before discharge), medication claims in the 3 monthsprior to admission are collected. The SDR for each classof medication (statins, antihypertensive, and antiplatelettherapies) will be recorded as secondary outcomes.Secondary outcomesIn a similar manner to the primary outcome, the propor-tion of participants adhering to medication will beassessed at 12 months. Self-reported outcomes will bemeasured by a trained research assistant during a tele-phone call at 6 and 12 months. Self-reported medicationadherence will be assessed using the Morisky 8-itemMedication Adherence Scale [48]. As per the Text4Heartpilot trial [32, 33], adherence to recommended lifestylebehaviors will be measured using a composite health be-havior score adapted from the EPIC-Norfolk ProspectivePopulation Study [49]. The following measures will beused to determine participants’ health behavior scores:1. Smoking status will be measured using three itemsfrom a validated smoking history questionnaire [50]including whether participants have ever smoked,have had a puff of tobacco in the last week andwhen they quit smoking (if appropriate)2. Physical activity level will be assessed using theGodin Leisure Time Physical Activity Questionnaire(GLTPAQ) [51]. This simple, three-item question-naire has well-established reliability and validity andhas been used in patients undergoing CR3. Alcohol consumption will be measured using theAlcohol Use Disorders Identification Test alcoholconsumption questions (AUDIT-C) [52]—ascreening tool designed to assess units of alcoholconsumed per week, and identify people who arehazardous drinkers. Index cards referencing standarddrink sizes will be used to reduce comprehensionerrors4. Fruit and vegetable intake are assessed by two NewZealand-specific questions used in the 2006/2007New Zealand Health Survey (n = 12,488, includingadults with CHD) [53]Participants receive a score on a 4-point scale for eachof the four key risk factors, with 1 point each assignedfor being a current non-smoker, meeting physical activityguidelines to achieve some health benefits (defined as ≥14 units on the GLTPAQ), consuming ≤ 14 standardunits of alcohol per week, and consuming at least fiveservings of fruit and vegetables per typical day.Using participants’ encrypted National Health Indexidentification numbers we will be able to obtain clinicaldata (lipid profiles and blood pressure) from theANZACS-QI database to maximize collection of theseoutcomes. Data describing hospital events, clinical infor-mation, as well as medication prescribing and dispensingwill also be captured. For the purpose of this trial we willaccess data on lipid profile (total/LDL/HDL cholesterol)and blood pressure, from admission and routine follow-ups. Using ANZACS-QI we will also be able to accessinformation on readmissions and related hospital events.Intervention delivery costs—including text-messageservice and per message costs as well as health servicestaff time for recruitment and program facilitation—willbe collected. Any changes in health service utilizationobserved between intervention and control groups willlead to an estimation of the costs of those changes withthe assistance of District Health Board funding informa-tion analysts.Adverse eventsAll participants will continue with their usual care forACS. No individual clinical advice is given through thepre-programmed text messages. We will be evaluatinghospitalizations or health service utilization as part ofthe outcomes specified above.Statistical analysisTrial data collected from all eligible participants will belinked with the national ANZACS-QI database usingparticipants’ encrypted National Health Index numberfor the purpose of analysis. Treatment evaluations willbe performed on the principle of intention-to-treat(ITT). Missing data on the primary outcome will be con-sidered as non-adherence in the ITT approach. Sensitiv-ity analyses will be conducted to test the robustness ofmain findings using different assumptions on the miss-ing data if the proportion of missing exceeds 10%. Theproportion of participants adhering to medication at6 months, with or without intervention, will first besummarized as frequency and percentage. Logisticregression will be conducted to evaluate the main treat-ment effect (OR and 95% CI), adjusting for pre-definedbaseline prognostic factors. For all secondary outcomescollected at 6 and 12 months post randomization, gener-alized linear regression models will be used to test theeffect of intervention between two groups, using a linkfunction appropriate to the distribution of outcomes.More specifically, an identity link will be used for con-tinuous outcomes under normal distribution and a logitlink for binary outcomes under binomial distribution.Regression models will adjust for baseline outcome value(where collected) and stratification factor. Model-adjusted estimate (mean difference for continuous out-comes and OR for binary outcomes) will be reported ateach scheduled visit, with 95% CI and associated p value.Maddison et al. Trials  (2018) 19:70 Page 6 of 10Missing data will not be imputed on secondary out-comes without adjustment for multiple testing. Statis-tical analysis will be performed using SAS version 9.4(SAS Institute Inc., Cary, NC, USA). All statistical testswill be two-sided at the 5% significance level.Cost-effectiveness analysisThis analysis will adopt a health system perspective. Wewill use the EQ-5D—a generic and validated measure ofquality of life for which reliable New Zealand populationpreference values are available—to obtain a single prefer-ence index for calculation of Quality-adjusted life-years(QALYs) to assess cost per QALY, for comparison withother programs. The incremental cost of making one extraparticipant adherent to CR using the intervention com-pared to usual care will be calculated. Ninety-five percentconfidence intervals for incremental cost-effectivenessratios, 95% confidence ellipses on the incremental cost-effectiveness plane, and cost-effectiveness acceptabilitycurves will be calculated to compare the intervention withusual care. Markov modeling will combine these data withother information from a systematic review of cost-effectiveness studies of CR to identify the long-term cost-effectiveness of the intervention.Data managementData will be entered into an electronic collection systemprovided by Enigma Solutions which will be linked tothe ANZACS-QI register. Range checks will be imple-mented and 10% of data will be checked for consistencyagainst source data.Evaluating implementationWe propose using the RE-AIM model proposed by Glas-gow and colleagues [34, 54] to determine uptake andsustainability of the intervention. The RE-AIM frame-work—which emphasizes collecting information aboutthe Reach, Effectiveness, Adoption, Implementation, andMaintenance of an intervention—is an evaluative frame-work for guiding the evaluation and reporting of healthintervention effectiveness [55]. Further, RE-AIM pro-vides a framework for determining which programswork under real-world conditions and which programsshould be sustained. The RE-AIM framework is an idealtool to use as the basis for planning and evaluating thesuccess of mobile phone self-management interventions[56, 57]. It also aligns with systems-based approachesand allows for assessment of vertical (e.g., adoption deci-sions within a given organization) and horizontal (e.g.,adoption across different sectors) components [58]. TheRE-AIM framework includes both individual- and set-ting/staff-level variables. Two dimensions operate at theindividual level (reach and effectiveness).A mixed-methods approach [59] will be used to assessthe key components of RE-AIM. Qualitative and quanti-tative data will be combined to thoroughly understandthe extent to which the self-management interventioncould be successfully implemented within the NewZealand health context [60]. To achieve this, data will becollected on each RE-AIM dimension as proposed byKessler et al. [61] and Glasgow [60]. Some of these datawill be collected as part of the trial (e.g., data to informreach, effectiveness and costs/resources). Additional datawill be collected specifically for the RE-AIM analysis(detailed below).To determine intervention reach, we will assess thenumber of people who participate as a proportion of thosewho are eligible, compare the characteristics of those whodo and do not participate, and provide detailed informa-tion of reach and recruitment issues [62, 63]. To achievethis, all potential participants approached about the studywill be screened and basic information collected. Thosewho decline participation will have their information per-manently de-identified. Screening information will be usedto determine the representativeness of those who agree toparticipate compared to those who decline. Qualitativedata will be gathered from those who decline about theirreasons for choosing to not participate. For those whoagree, a brief semi-structured interview will be conductedto determine their perspectives of the proposed interven-tion, their current self-management behaviors, and anyconcerns they might have that would have impacted ontheir involvement or adoption.In addition to the primary outcome, biological-, psy-chosocial-, demographic-, and program-specific parame-ters will be assessed as potential moderators ofintervention effectiveness.RE-AIM dimensions Adoption, Implementation, andMaintenance will be assessed from both provider andorganizational perspectives [54]. Key informant inter-views will be conducted with stakeholders (medical prac-titioners and allied health staff ) to obtain qualitativedata from providers across these three RE-AIM dimen-sions, to determine factors that may enhanceorganizational adoption and maintenance, and potentialadaptations to heighten the likelihood of consistent de-livery across providers and locations. Quantitativeassessment of implementation will be determined bymeasuring text-message responses where appropriate.Maintenance at the organizational level will be deter-mined by conducting key informant interviews withstakeholders (e.g., chief executive officers) as well as gov-ernment and non-government agencies (Ministry ofHealth, Heart Foundation) examining potential sustain-ability options for each organization [64]. To evaluateMaintenance at the patient level, patient outcomes willbe measured at 12 months via ANZACS-QI. Long-termMaddison et al. Trials  (2018) 19:70 Page 7 of 10attrition (%) and differential rates by patient characteris-tics or treatment condition will be examined. At theorganizational level, we will collect data on whether theinterventions were sustained at more than 6 monthspost study funding, or which elements were retainedafter the program was funded.Qualitative data collection and analysis will be con-ducted by a trained and experienced researcher. Inter-views will be digitally recorded and transcribed. Datawill be entered using NVivo software to enable qualita-tive analysis. An inductive analysis approach will be usedto identify the key themes to emerge from the data.These data will be collated according to each domain ofthe RE-AIM framework. These data sources will be com-bined and—together with the advisory group—investiga-tors will make recommendations to determine theextent to which the self-management interventionachieved the desired RE-AIM outcomes. This approachhas been successfully used with other behavior-changeinterventions and will also be valuable for informingoptimal scenarios for funding and implementing thisself-management program [54, 65, 66].DiscussionThe Text4Heart II trial will determine the effectivenessof a text-message-based intervention in addition to usualcare for improving adherence to medication and lifestylebehaviors at both 6 and 12 months. Using the RE-AIMframework this trial will provide much needed data andinsight into the potential implementation of Text4HeartII to augment existing cardiac services within two majormetropolitan hospitals. The protocol, in accordance withthe SPIRIT Statement, includes outcomes from recentsystematic reviews of mobile health with the aim of add-ing quality evidence to the body of academic literature.This trial addresses many limitations/criticisms of pre-vious mHealth trials [43, 67]; it builds on the Text4Heartpilot trial, is adequately powered, has sufficient durationto elicit behavior change, and the follow-up assessments(6 and 12 months) are long enough to determine thesustained effect of the intervention. We also outline thebehavior-change theory used, and intervention content,which will enhance its replicability. Using data linkage(National Pharmaceuticals Collection and ANZACS-QIregistries) our Text4Heart II trial will not only providean objective measurement of medication adherence, butwill be one of the first of its kind to provide muchneeded data on sustained effects on clinical outcomesincluding hospitalization and mortality. While mHealthis often touted as a low-cost intervention that can be de-livered at scale, few studies provide evidence of this. TheText4Heart II trial will also provide much needed dataon the cost-effectiveness of this approach, and its poten-tial implementation and scalability as a national service.In summary, Text4Heart II should produce new know-ledge on the effectiveness and cost-effectiveness of aninnovative and promising mHealth program to improveself-management of heart disease. It extends previousresearch by investigating the sustained effects of a text-message intervention, and will offer unique insights intoclinical effects. If effective, this approach could substan-tially reduce deaths and hospital admissions in a groupof patients who account for up to one third of all hos-pital admissions. We will provide much needed insightinto the potential of implementing this program at anational level, thereby augmenting existing CVD servicedelivery.Trial statusRecruitment for the Text4Heart II trial opened in July2016 at Auckland City and North Shore Hospitals(Auckland, New Zealand). Recruitment is currentlyopen, and expected to be completed in October 2017.The original study protocol was finalized on 18 March2016; this manuscript reports version 5, amended on 13December 2016. The primary amendment extendedfollow-up to 12 months, facilitated by an award fromNational Heart Foundation of New Zealand. Versioncontrol has been implemented to document all amend-ments to the study protocol, and these will be communi-cated to the Ethics Committees and trial investigators asrequired.Additional fileAdditional file 1: SPIRIT Checklist. (DOC 120 kb)AbbreviationsACS: Acute coronary syndrome; ANZACS-QI: All New Zealand Acute CoronarySyndrome Quality Improvement register; AUDIT-C: Alcohol Use DisordersIdentification Test; CHD: Coronary heart disease; CR: Cardiac rehabilitation;CVD: Cardiovascular disease; GLTPAQ: Godin Leisure Time Physical ActivityQuestionnaire; ITT: Intention-to-treat; LDL: Low-density lipoprotein;MI: Myocardial infarction; OR: Odds ratio; QALY: Quality-adjusted life-year;SDR: Medication Dispensing Ratio; SMS: Short message serviceAcknowledgementsNot applicableFundingFinancial support for this trial is being provided by the Health ResearchCouncil of New Zealand (15/667) and National Heart Foundation of NewZealand (1684). In-kind support is being provided by the Auckland andWaitemata District Health Boards. Funders will have no involvement in thestudy design; data collection, management, analysis, and interpretation;report writing; or decision to submit the reports for publication.Availability of data and materialsNot applicableDissemination policyA dissemination policy has yet to be finalized and signed by all investigators,but will include peer reviewed publications, conference presentations, and amedia release.Maddison et al. Trials  (2018) 19:70 Page 8 of 10Authors’ contributionsRM conceived of the study, its design, and led drafting of the manuscript. RScontributed clinical expertise for the trial design and refined the studyprotocol. RD contributed clinical expertise for the trial design and refined thestudy protocol. TS contributed clinical expertise for the trial design andrefined the study protocol. AK contributed clinical expertise for the trialdesign and refined the study protocol. JB contributed clinical expertise forthe trial design and refined the study protocol. RW contributed to the trialdesign and refinement of the study protocol. JR contributed to the trialdesign and refinement of the study protocol. AR contributed to the trialdesign and refinement of the study protocol. YJ contributed statisticalexpertise and will conduct the primary analyses. PE contributed to the trialdesign and refinement of the study protocol. RKS contributed to the trialdesign and refinement of the study protocol. HB contributed to the trialdesign and refinement of the study protocol. LPD contributed to the trialdesign and refinement of the study protocol. All authors read and approvedthe final manuscript.Ethics approval and consent to participateText4Heart II received ethical approval from the New Zealand Health andDisability Ethics Committee, Northern A (15/NTA/205); internal approval wasalso granted by the Auckland and Waitemata District Health Board ResearchReview Committees. All participants will provide written or verbal consent asdescribed above.Consent for publicationNot applicableCompeting interestsThe authors declare that they have no competing interests.Publisher’s NoteSpringer Nature remains neutral with regard to jurisdictional claims inpublished maps and institutional affiliations.Author details1Institute for Physical Activity and Nutrition, Deakin University, Geelong, VIC,Australia. 2Department of Cardiology, Auckland District Health Board,Auckland, New Zealand. 3Heart Health Research Group, Department ofMedicine, University of Auckland, Auckland, New Zealand. 4Department ofCardiology, Waitemata District Health Board, Auckland, New Zealand.5Epidemiology and Biostatistics, University of Auckland, Auckland, NewZealand. 6National Institute for Health Innovation, School of PopulationHealth, University of Auckland, Auckland, New Zealand. 7The Centre forHealth, Tauranga, New Zealand. 8Department of Health Promotion, Socialand Behavioral Health, University of Nebraska Medical Centre, Omaha, NE,USA. 9Department of Exercise Sciences, Faculty of Science, University ofAuckland, Auckland, New Zealand. 10School of Kinesiology, University ofBritish Columbia, Vancouver, BC, Canada.Received: 27 July 2017 Accepted: 11 January 2018References1. World Health Organisation: Cardiovascular diseases (CVDs): Fact sheet[http://www.who.int/mediacentre/factsheets/fs317/en/index.html andarchived at http://www.webcitation.org/6whJmvZ1h.2. Chan WC, Wright C, Riddell T, Wells S, Kerr AJ, Gala G, Jackson R. Ethnic andsocioeconomic disparities in the prevalence of cardiovascular disease inNew Zealand. N Z Med J. 2008;121(1285):11–20.3. National Center for Chronic Disease Prevention and Health. Heart Disease andStroke Prevention: Addressing the Nation's Leading Killers: At A Glance 2011. In.Georgia, USA: Centers for Disease Control and Prevention; 2011.4. Australian Institute of Health and Welfare. Cardiovascular, diabetes andchronic kidney disease series. Canberra, Australia: AIHW; 2014.5. Mozaffarian D, Benjamin EJ, Go AS, Arnett DK, Blaha MJ, Cushman M, deFerranti S, Despres JP, Fullerton HJ, Howard VJ, et al. Heart disease andstroke statistics—2015 update: a report from the American HeartAssociation. Circulation. 2015;131(4):e29–e322.6. World Health Organisation: Non-communicable diseases: Factsheet.http://www.who.int/mediacentre/factsheets/fs355/en/ and archived athttp://www.webcitation.org/6whLfLksM.7. Taylor R, Kirby B. The evidence base for the cost-effectiveness of cardiacrehabilitation. Heart. 1997;78(1):5–6.8. Gardetto N. Self-management in heart failure: where have we been andwhere should we go? J Multidiscip Healthc. 2011;4:39–51.9. Wong WP, Feng J, Pwee KH, Lim J. A systematic review of economicevaluations of cardiac rehabilitation. BMC Health Serv Res. 2012;12:243.10. Jolliffe J, Rees K, Taylor RRS, Thompson DR, Oldridge N, Ebrahim S: Exercise-based rehabilitation for coronary heart disease. Cochrane Database Sys Rev.2009(1). https://doi.org/10.1002/14651858.CD14001800.11. Iestra JA, Kromhout YT, Schouw VD, Grobbee DE, Boshuizen HC, vanStaveren WA. Effect size estimates of lifestyle and dietary changes on all-cause mortality in coronary artery disease patients: a systematic review.Circulation. 2005;112:924–34.12. Bethell HJN, Evans JA, Turner SC, Lewin RJ. The rise and fall of cardiacrehabilitation in the United Kingdom since 1998. J Public Health. 2006;29(1):57–61.13. Bethell HJN, Lewin RJ, Dalal HM. Cardiac rehabilitation in the UnitedKingdom. Heart. 2009;95:271–5.14. Suaya JA, Shepard DS, Normand S-LT, Ades PA, Prottas J, Stason WB. Use ofcardiac rehabilitation by Medicare beneficiaries after myocardial infarctionor coronary bypass surgery. Circulation. 2007;116(15):1653–62. https://doi.org/10.1161/circulationaha.107.701466.15. Banerjee AT, Gupta M, Singh N. Patient characteristics, compliance, andexercise outcomes of South Asians enrolled in cardiac rehabilitation. JCardiopulm Rehabil Prev. 2007;27(4):212–18. https://doi.org/10.1097/01.HCR.0000281765.52158.be.16. Walters DL, Aroney CN, Chew DP, Bungey L, Coverdale SG, Allan R, BriegerD. Variations in the application of cardiac care in Australia. Med J Aust. 2008;188(4):218–23.17. Doolan-Noble F, Broad J, Riddell T, North D. Cardiac rehabilitation servicesin New Zealand: access and utilisation. N Z Med J. 2004;117(1197):1–12.18. Bethell HJN. Exercise in cardiac rehabilitation. Br J Sports Med. 1999;33:79–86.19. Daly J, Sindone AP, Thompson DR, Hancock K, Chang E, Davidson P.Barriers to participation in and adherence to cardiac rehabilitationprograms: a critical literature review. Prog Cardiovasc Nurs. 2002;17(1):8–17.https://doi.org/10.1111/j.0889-7204.2002.00614.x.20. Dunlay S, Witt B, Allison T, Hayes S, Weston S, Koepsell E, Roger V. Barriersto participation in cardiac rehabilitation. Am Heart J. 2009;158(5):852–9.21. Beswick AD, Rees K, West RR, Taylor FC, Burke M, Griebsch I, Taylor RS,Victory J, Brown J, Ebrahim S. Improving uptake and adherence incardiac rehabilitation: literature review. J Adv Nurs. 2005;49(5):538–55.https://doi.org/10.1111/j.1365-2648.2004.03327.x.22. Clark R, Conway A, Poulsen V, Keech W, Tirimacco R, Tideman P. Alternativemodels of cardiac rehabilitation: a systematic review. Eur J Prev Cardiol.2015;22(1):35–74.23. Dalal HM, Evans P. Achieving national service framework standards forcardiac rehabilitation and secondary prevention. Br Med J. 2003;326:481–4.24. Neubeck L, Redfern J, Fernandez R, Briffa T, Bauman A, Freedman SB.Telehealth interventions for the secondary prevention of coronary heartdisease: a systematic review. Eur J Cardiovasc Prev Rehabil. 2009;16:281–9.https://doi.org/10.1097/HJR.0b013e32832a4e7a.25. Pfaeffli Dale L, Dobson R, Whittaker R, Maddison R. The effectiveness ofmobile-health behaviour change interventions for cardiovascular diseaseself-management: a systematic review. Eur J Prev Cardiol. 2016;23(8):801–17.26. Cole-Lewis H, Kershaw T. Text messaging as a tool for behavior change indisease prevention and management. Epidemiol Rev. 2010;32(1):56–69.https://doi.org/10.1093/epirev/mxq004.27. Krishna S, Boren S, Balas E. Healthcare via cell phones: a systematic review.Telemed J E Health. 2009;15:231–40.28. Fjeldsoe BS, Marshall AL, Miller YD. Behavior change interventions deliveredby mobile phone telephone short-message service. Am J Prev Med. 2009;36(2):165–73.29. Maddison R, Pfaeffli L, Whittaker R, Stewart R, Kerr A, Jiang Y, Rawstorn J,Carter K, Whittaker R. The HEART mobile phone trial: the partial mediatingeffects of self-efficacy on physical activity among cardiac patients. FrontPublic Health. 2014;2:27. https://doi.org/10.3389/fpubh.2014.00056.30. Maddison R, Pfaeffli L, Whittaker R, Stewart R, Kerr AJ, Jiang A, Kira G, LeungW, Dalleck L, Carter KH, et al. A mobile phone intervention increasesMaddison et al. Trials  (2018) 19:70 Page 9 of 10physical activity in people with cardiovascular disease: results from theHEART randomised controlled trial. Eur J Prev Cardiol. 2014. https://doi.org/10.1177/2047487314535076.31. Chow C, Redfern J, Hillis G, Thakkar J, Santo K, Hackett ML, Jan S, Graves N,de Keizer L, Barry T, et al. Effect of lifestyle-focused text messaging on riskfactor modification in patients with coronary heart disease: a randomizedclinical trial. J Am Med Assoc. 2015;314(12):1255–66. https://doi.org/10.1001/jama.2015.10945.32. Pfaeffli Dale L, Whitatker R, Jiang Y, Stewart R, Rolleston A, Maddison R.Improving coronary heart disease self-management using mobiletechnologies (Text4Heart): a randomised controlled trial protocol. Trials.2014;15:71. https://doi.org/10.1186/1745-6215-15-71.33. Dale L, Whittaker R, Jiang Y, Stewart R, Rolleston A, Maddison R. Textmessage and internet support for coronary heart disease self-management:results from the Text4Heart randomized controlled trial. J Med Internet Res.2015;17(10):e237. https://doi.org/10.2196/jmir.4944.34. Glasgow R, McKay H, Piette J, Reynolds K. The RE-AIM Framework forevaluating interventions: what can it tell us about approaches to chronicillness management? Patient Educ Couns. 2001;44:119–27.35. Chan A, Tetzlaff J, Altman D, Laupacis A, Gøtzsche P, Krleža-Jerić K,Hróbjartsson A, Mann H, Dickersin K, Berlin J, et al. SPIRIT 2013 statement:defining standard protocol items for clinical trials. Ann Intern Med. 2013;158(3):200-207. https://doi.org/10.7326/0003-4819-158-3-201302050-00583.36. Eysenbach G, CONSORT-EHEALTH Group. CONSORT-EHEALTH: improvingand standardizing evaluation reports of web-based and mobile healthinterventions. J Med Internet Res. 2011;13:e126. https://doi.org/10.2196/jmir.1923.37. Kerr A, Williams M, White H, Doughty R, Nunn C, Devlin G, Grey C, Lee M,Flynn C, Rhodes M, et al. The All New Zealand Acute Coronary SyndromeQuality Improvement Programme: implementation, methodology andcohorts (ANZACS-QI 9). N Z Med J. 2016;5(129):23–36.38. Kerr AJ, McLachlan A, Furness S, Broad J, Riddell T, Jackson R, Wells S. Theburden of modifiable cardiovascular risk factors in the coronary care unit byage, ethnicity, and socioeconomic status—PREDICT CVD-9. N Z Med J. 2008;121(1285):20–33.39. Thornley S, Marshall R, Chan WC, Kerr AJ, Harrison J, Jackson G, Crengle S,Wright C, Wells S, Jackson R. Four out of ten patients are not taking statinsregularly during the 12 months after an acute coronary event. Eur JCardiovasc Prev Rehabil. 2011;19(3):349-57. https://doi.org/10.1177/1741826711403069.40. Pfaeffli Dale L, Whittaker R, Eyles H, Ni Mhurchu C, Ball K, Smith N, Maddison R.Cardiovascular disease self-management: pilot testing of an mHealth eatingprogram. Pers Med. 2014;4:88–101. https://doi.org/10.3390/jpm4010088.41. Bramley D, Riddell T, Whittaker R, Corbett T, Lin R-B, Wills M, Jones M,Rodgers A. Smoking cessation using mobile phone text messaging is aseffective in Maori as non-Maori. N Z Med J. 2005;118(1216):74-83. http://www.nzma.org.nz/journal/118-1216/1494/.42. Rodgers A, Corbett T, Bramley D, Riddell T, Wills M, Lin R-B, Jones M. Do usmoke after txt? Results of a randomised trial of smoking cessation usingmobile phone text messaging. Tob Control. 2005;14(4):255–61.43. Free C, Knight R, Robertson S, Whittaker R, Edwards P, Zhou W, Rodgers A,Cairns J, Kenward M, Roberts I. Smoking cessation support delivered viamobile phone text messaging (txt2stop): a single-blind, randomised trial.Lancet. 2011;378(9785):49–55.44. Leventhal H, Meyer D, Nerenz DR. The common sense representation ofillness danger. In: Rachman S, editor. Contributions to Medical Psychology.New York: Pergamon; 1980. p. 7–30.45. Bandura A. Human agency in social cognitive theory. Am Psychol. 1989;44:1175–84.46. Broadbent E, Ellis CJ, Thomas J, Gamble G, Petrie KJ. Further developmentof an illness perception intervention for myocardial infarction patients: arandomised controlled trial. J Psychosom Res. 2009;67(1):17–23.47. New Zealand Guidelines Group: Best Practice Evidence-based Guideline: TheAssessment and Management of Cardiovascular Risk. Wellington, NewZealand: New Zealand Guidelines Group; 2003.48. Morisky D, Ang A, Krousel-Wood M, Ward H. Predictive validity of a medicationadherence measure in an outpatient setting. J Clin Hypertens. 2008;10(5):348–54.49. Khaw K, Wareham N, Bingham S, Welsch A, Luben R, Day N. Combinedimpact of health behaviours and mortality in men and women: The EPIC-Norfolk Prospective Population Study. PLoS Med. 2008;5(1):e12.50. Maddison R, Roberts V, Bullen C, McRobbie H, Jiang Y, Prapavessis H, GloverM, Taylor S, Brown P. Design and conduct of a pragmatic randomizedcontrolled trial to enhance smoking-cessation outcomes with exercise: TheFit2Quit study. Ment Health and Phys Act. 2010;3(2):92–101. https://doi.org/10.1016/j.mhpa.2010.09.003.51. Godin G, Shephard RJ. A simple method to assess exercise behavior in thecommunity. Can J Appl Sport Sci. 1985;10(3):141–6.52. Bush K, Kivlahan DR, McDonell MB, Fihn SD, Bradley KA. The AUDITalcohol consumption questions (AUDIT-C): an effective brief screeningtest for problem drinking. Ambulatory Care Quality ImprovementProject (ACQUIP). Alcohol Use Disorders Identification Test. Arch InternMed. 1998;158(16):1789–95.53. Ministry of Health. New Zealand Health Survey 2006/07 Adult Questionnaire.Wellington: Ministry of Health; 2008.54. Glasgow R, Klesges L, Dzewaltowski D, Estabrooks P, Vogt T. Evaluating theimpact of health promotion programs: using the RE-AIM framework to formsummary measures for decision making involving complex issues. HealthEduc Res. 2006;21(5):688–94.55. Allen K, Zoellner J, Motley M, Estabrooks PA. Understanding the internal andexternal validity of health literacy interventions: a systematic literaturereview using the RE-AIM framework. J Health Commun. 2011;16(3):55–72.56. Estabrooks P, Fisher E, Hayman L. What is needed to reverse the trends inchildhood obesity? A call to action. Ann Behav Med. 2008;36(3):209–16.https://doi.org/10.1007/s12160-008-9070-757. Klesges L, Estabrooks P, Dzewaltowski D, Bull S, Glasgow R. Beginning withthe application in mind: designing and planning health behavior changeinterventions to enhance dissemination. Ann Behav Med. 2005;29(2):66–75.https://doi.org/10.1207/s15324796abm2902s_10.58. Estabrooks PA, Glasgow RE. Translating effective clinic-based physicalactivity interventions into practice. Am J Prev Med. 2006;31(4):S45–56.https://doi.org/10.1016/j.amepre.2006.06.019.59. Evans B, Snooks H, Howson H, Davies M. How hard can it be to includeresearch evidence and evaluation in local health policy implementation?Results from a mixed methods study. Implement Sci. 2013;8(17).https://doi.org/10.1186/1748-5908-8-17.60. Glasgow RE: What does it mean to be pragmatic? Pragmatic methods,measures, and models to facilitate research translation. Health Educ Behav.2013;40(3):257–65. https://doi.org/10.1177/1090198113486805.61. Kessler R, Purcell E, Glasgow RE, Klesges L, Benkeser RM, Peek C. What doesit mean to employ the RE-AIM model? Eval Health Prof. 2012;36(1):44–66.https://doi.org/10.1177/0163278712446066.62. Estabrooks P, Shoup JA, Gattshall M, Dandamudi P, Shetterly S, Xu S.Automated telephone counseling for parents of overweight children: arandomized controlled trial. Am J Prev Med. 2009;36:35–42. https://doi.org/10.1016/j.amepre.2008.09.024.63. Pinard C, Hart M, Hodgkins Y, Serrano E, McFerren M, Estabrooks P. Smartchoices for healthy families: a pilot study for the treatment of childhoodobesity in low-income families. Health Educ Behav. 2012;39(4):433–45.64. Estabrooks P, Smith-Ray R, Dzewaltowski D, Dowdy D, Lattimore D,Rheaume C, Ory M, Bazzarre T, Griffin S, Wilcox S: Sustainability of evidence-based community-based physical activity programs for older adults: lessonsfrom Active for Life. Translational Behavioral Medicine 2011;1(2):208–15.https://doi.org/10.1007/s13142-011-0039-x.65. Glasgow RE, Vogt TM, Boles SM. Evaluating the public health impact ofhealth promotion interventions: the RE-AIM framework. American Journal ofPublic Health 1999;89(9):1322–27.66. Glasgow RE, Askew S, Purcell P, Levine E, Warner ET, Strange KC, Colditz GA,Bennett GG: Use of REAIM to address health inequalities: Application in alow-income community health centre-based weight loss and hypertensionself-managment program. Translational Behavioral Medicine 2013;3(2):200–10.67. Kaplan R, Stone A. Bringing the laboratory and clinic to the community:mobile technologies for health promotion and disease prevention. AnnuRev Psychol. 2013;64:471–98. https://doi.org/10.1146/annurevpsych-113011-143736.Maddison et al. Trials  (2018) 19:70 Page 10 of 10

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