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High blood pressure is a major risk factor for global disease burden.1 Even modest reductions in blood pressure are

important and would reduce the risk of associated morbidity and premature mortality.2–4 In settings where health care and medicines are freely available, a substantial burden of cardio-vascular disease may be attributable to suboptimal adherence

to blood pressure–lowering treatments.5 Missed appointments for collection of medicine and challenges with taking life-long treatment are some of the major reasons for suboptimal

Background—We assessed the effect of automated treatment adherence support delivered via mobile phone short message system (SMS) text messages on blood pressure.

Methods and Results—In this pragmatic, single-blind, 3-arm, randomized trial (SMS-Text Adherence Support [StAR]) undertaken in South Africa, patients treated for high blood pressure were randomly allocated in a 1:1:1 ratio to information only, interactive SMS text messaging, or usual care. The primary outcome was change in systolic blood pressure at 12 months from baseline measured with a validated oscillometric device. All trial staff were masked to treatment allocation. Analyses were intention to treat. Between June 26, 2012, and November 23, 2012, 1372 participants were randomized to receive information-only SMS text messages (n=457), interactive SMS text messages (n=458), or usual care (n=457). Primary outcome data were available for 1256 participants (92%). At 12 months, the mean adjusted change in systolic blood pressure compared with usual care was −2.2 mm Hg (95% confidence interval, −4.4 to −0.04) with information-only SMS and −1.6 mm Hg (95% confidence interval, −3.7 to 0.6) with interactive SMS. Odds ratios for the proportion of participants with a blood pressure <140/90 mm Hg were 1.42 (95% confidence interval, 1.03–1.95) for information-only messaging and 1.41 (95% confidence interval, 1.02–1.95) for interactive messaging compared with usual care.

Conclusions—In this randomized trial of an automated adherence support program delivered by SMS text message in a general outpatient population of adults with high blood pressure, we found a small reduction in systolic blood pressure control compared with usual care at 12 months. There was no evidence that an interactive intervention increased this effect.

Clinical Trial Registration—URL: http://www.clinicaltrials.gov. Unique identifier: NCT02019823. South African National Clinical Trials Register, number SANCTR DOH-27-1212-386; Pan Africa Trial Register, number PACTR201411000724141. (Circulation. 2016;133:592-600. DOI: 10.1161/CIRCULATIONAHA.115.017530.)

Key Words: behavior therapy ◼ delivery of health care ◼ patient compliance ◼ randomized controlled trial ◼ self care

Circulation is available at http://circ.ahajournals.org DOI: 10.1161/CIRCULATIONAHA.115.017530

Continuing medical education (CME) credit is available for this article. Go to http://cme.ahajournals.org to take the quiz. Received May 28, 2015; accepted December 23, 2015.From Institute of Biomedical Engineering, Department of Engineering Science (K.B., D.S., T.B., L.T.) and Nuffield Department of Primary Care Health

Sciences (K.B., A.J.F., M.S., L.-M.Y.), University of Oxford, UK; Chronic Disease Initiative for Africa, Cape Town, South Africa (K.B., K.S., N.L.); Division of Nephrology and Hypertension, Groote Schuur Hospital, Cape Town, South Africa (B.R.); University of Cape Town, South Africa (B.R.); Western Cape Province Department of Health, Cape Town, South Africa (M.N.); and Division of Diabetic Medicine and Endocrinology, Department of Medicine, University of Cape Town, South Africa (N.L., K.B.).

*Drs Bobrow and Farmer contributed equally.The online-only Data Supplement is available with this article at http://circ.ahajournals.org/lookup/suppl/doi:10.1161/CIRCULATIONAHA.

115.017530/-/DC1.Correspondence to Andrew J. Farmer, DM, Nuffield Department of Primary Care Health Sciences, University of Oxford, Radcliffe Observatory Quarter,

Oxford OX2 6GG, UK. E-mail andrew.farmer@phc.ox.ac.uk© 2016 American Heart Association, Inc.

Mobile Phone Text Messages to Support Treatment Adherence in Adults With High Blood Pressure

(SMS-Text Adherence Support [StAR])A Single-Blind, Randomized Trial

Kirsten Bobrow, DPhil*; Andrew J. Farmer, DM*; David Springer, MSc; Milensu Shanyinde, MSc; Ly-Mee Yu, DPhil; Thomas Brennan, DPhil; Brian Rayner, PhD; Mosedi Namane, MPhil; Krisela Steyn, MD; Lionel Tarassenko, DPhil; Naomi Levitt, MD

Editorial see p 555 Clinical Perspective on p 600

Hypertension

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Bobrow et al SMS Text Adherence Support for High Blood Pressure 593

adherence.6 Adherence support delivered via short message system (SMS) text messages has the potential to improve treat-ment adherence and health outcomes.7 Some but not all inter-ventions delivered by SMS have been effective at improving adherence and clinical outcomes, for example, in HIV-infected patients in low-resource settings.8 However, there is no evi-dence that SMS-based interventions are effective in improv-ing treatment adherence and clinical outcomes for high blood pressure in low-resource settings.9 We carried out an effective-ness trial (SMS-Text Adherence Support [StAR]) to establish whether adherence support delivered via SMS text messages through information-only or interactive SMS text messaging is better than usual care in maintaining and improving treatment adherence and blood pressure control.

MethodsStudy Design and ParticipantsWe carried out a parallel, 3-group, randomized, controlled trial among the general adult population attending the outpatient chronic disease services in a single, large, public-sector clinic in Cape Town, South Africa. This primary care facility provides a range of healthcare ser-vices to an ethnically diverse, socioeconomically deprived population from 2 communities. According to 2011 Census data, the ethnicity of these communities is mostly black African (51%) or mixed ancestry (48%), about one third of households live in informal dwellings or shacks, and 64% of households have a monthly income of less than R3500.00 (about $270.00). The clinic is within walking distance of both communities. All primary healthcare services and medicines are provided free of charge. In the chronic disease services, stable patients on treatment are reviewed by a clinician (doctor or prescrib-ing nurse) every 3 to 6 months, although patients initiating treatment for the first time or those with a blood pressure >140/90 mm Hg are reviewed more frequently.

At clinical review, patients are prescribed medication on repeat until their next scheduled review. The medications available for first-line prescription are enalapril, thiazide diuretic, and amlodipine. If blood pressure remains uncontrolled, then β- or α-blockers and occasionally spironolactone are added. Medicines are dispensed for 28-day periods, and patients collect these from the onsite pharmacy. Patients on a stable regimen with a valid repeat prescription receive their monthly supply of medicines prepackaged from the Chronic Dispensing Unit, a centralized service through which the supplies are delivered to the clinic pharmacy 48 hours before a patient’s scheduled collection date. Medicines not collected are returned to the Chronic Dispensing Unit 72 hours after the scheduled appointment. The trial protocol, including an outline of the statistical analysis plan, has pre-viously been published.10

We enrolled adults (≥21 years of age) who had the following characteristics: diagnosed with hypertension by a clinician using local guidelines, prescribed blood pressure–lowering medication, and with a systolic blood pressure (SBP) <220 mm Hg and a diastolic blood pressure <120 mm Hg at enrollment. Eligible patients were attending the primary care clinic, resided in 1 of the 2 study com-munities, and had regular access to a mobile phone (and were able to send SMS text messages or could do so with help of a relative). We enrolled only 1 member per household. The following patients were excluded: those requiring specialist care for their hypertension at a hospital (in secondary care), women who self-reported being pregnant or within 3 months postpartum, and those with very high blood pressures (SBP >220 mm Hg or diastolic blood pressure >120 mm Hg) who had symptoms suggestive of a hypertensive emergency or were otherwise acutely unwell (who were directly referred to the appropriate clinical service).

Clinic staff who measured the vital signs of all patients attending the chronic disease services for a clinical review identified potential participants. Trained research assistants assessed trial eligibility for patients who had agreed to be referred to the trial, and those eligible

were enrolled. Participants received an SMS text message at the time of recruitment to confirm their enrollment in the trial. All partici-pants were subsequently sent non–health-related messages at 6-week intervals.

The trial was approved by the Human Research Ethics Committee of the University of Cape Town (HREC UCT 418/2011), the Oxford Tropical Research Ethics Committee (OXTREC 03–12), and the Metro District Health Services, Western Cape (RP 141/2011). Trial conduct was overseen by a trial steering committee. All participants provided written informed consent, and the trial was conducted in accordance with the Helsinki Declaration of 2008.

Randomization and MaskingTrained research staff collected baseline data immediately before enrollment, and an independent administrator entered these data into a secure, Web-based randomization database implemented by the Primary Care Clinical Trials Unit in Oxford. A software algorithm assigned participants independently of the research team to informa-tion-only adherence support, interactive adherence support, or usual care in a 1:1:1 ratio using a nondeterministic minimization algorithm to ensure balance between groups with respect to age, sex, baseline SBP, years with hypertension, and recent clinic attendance.11 Trial statisticians, researchers, clinic staff, and research assistants who col-lected outcome data were masked to allocated interventions until the trial database was locked. Researchers and clinicians were not aware of randomization assignment, were trained not to ask patients about the content of messages, and were unable to determine randomization group from casual comments by participants. Blood pressure mea-surements were automated, and data were captured directly to the trial database.

ProceduresAll participants received written information about hypertension and healthy living and continued to receive care from the clinic. Personalized SMS text messages were sent to information-only mes-sage and interactive message group participants at weekly intervals at a time and in a language selected by the participant. We iteratively designed, developed, and tested 2 SMS text messaging–based inter-ventions with clinical staff and patients with high blood pressure working and living in low-income communities around Cape Town.12 The messages were designed to address a range of common issues with adherence to and persistence with treatment.13 We developed a library of SMS text messages, which we mapped to a taxonomy of behavior change techniques (Table I in the online-only Data Supplement).14 Most of the messages focused on the techniques of goals and planning, repetition and substitution, social support, and natural consequences. The SMS text messages used in the interven-tions were developed, translated, and tested in English, isiXhosa, and Afrikaans, the 3 languages most commonly spoken by people living in Cape Town.

The information-only adherence support group members were sent messages to motivate collecting and taking medicines and to provide education about hypertension and its treatment. Additional reminders were sent when medicines were ready for collection or for scheduled clinic appointments. All trial participants were given a phone number to contact the research team.

Participants allocated to the interactive adherence support received the same messages as the information-only group but could also respond to selected messages using free-to-user “please call me” requests. These generated an automated series of responses from the text message delivery system offering trial participants a number of options, including canceling or changing an appointment and chang-ing the timing and language of the text messages.

All trial materials, including information sheets, consent forms, and the SMS text messages, were also developed, translated, and tested in English, isiXhosa, and Afrikaans.

All SMS text messages were delivered automatically via an open-source Web-based electronic medical record system (OpenMRS ver-sion 1.6.1, OpenMRS Ltd, Grandville, MI). All participant data were

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594 Circulation February 9, 2016

captured in the clinic and uploaded to OpenMRS with Sana Mobile (Sana, MIT, Cambridge, MA), an open-source Android platform.10,15 Timing of messages relating to clinic appointments and medicine collection was facilitated by secure linkage to computerized appoint-ment data.

Messages were sent for 1 year from enrollment. Blood pressure measurements were collected from participants as they attended their routine clinic visits, but otherwise no additional measurements or interventions were carried out during the trial. Delivery of SMS text messages was automatically tracked, and if a message was undeliv-ered, a research assistant blinded to group allocation contacted the number of a friend or relative to obtain a new mobile phone number. Table II in the online-only Data Supplement provides a structured description of the intervention and its development.16

The primary clinical outcome was the change in mean SBP measured at baseline and 12 months with a validated oscillometric device,10 adapted to record 6 sequential readings at 3-minute inter-vals. The mean blood pressure was calculated by discarding the initial reading and calculating the mean from the 5 remaining readings.17

Treatment adherence was assessed by calculating the proportion of days of medication covered, a proxy measure of adherence, from prescribing and dispensing data routinely recorded in the clinical record, pharmacy record, and Chronic Dispensing Unit record.18,19 When there were discrepancies in data on dispensing, we used a computer-based algorithm blinded to randomized group to assign the status (dispensed/not dispensed) favoring any evidence that the medi-cation had been dispensed. Proportion of days of medication covered was summarized as the proportion of patients with ≥80% of days covered with blood pressure–lowering medication on the basis of a systematic review providing evidence for the clinical importance of this threshold5 and reported in 3-month intervals and over 12 months.

Additional secondary outcomes measured at 12 months, specified in the protocol,10 were proportion of participants achieving a mean SBP <140 mm Hg and a mean diastolic blood pressure <90 mm Hg, health status measured with the EuroQol Group 5-Dimension Self-Report Questionnaire,20 proportion of scheduled clinic appointments attended, retention in clinical care, satisfaction with clinic services and care, hospital admissions, self-reported adherence to medication (score range, 5–10),21 and basic hypertension knowledge.22 Data were also collected on the number and type of medication changes made during the trial and numbers of clinic visits by participants.

Statistical AnalysisThe intended target sample size of 1215 participants, allowing 20% loss to follow-up (at least 405 in each group), was estimated to detect an absolute mean difference in SBP of 5 mm Hg (SD, 22 mm Hg; a clinically important reduction in the relative risk of stroke and coro-nary heart disease events)23 at 12 months from baseline, with 90% power and 0.05 (2-sided) level of significance. All analyses were per-formed on an intention-to-treat basis.

We analyzed the 12-month primary outcome using a mixed-effect model for repeated measures including data available on all random-ized patients attending follow-up visits at 6 and 12 months. The method has the advantage of implicitly accounting for the mecha-nism of data missing at random by using maximum likelihood. In the model, participant-specific intercepts were fitted with the use of random effects, and time and treatment were modeled with the use of fixed effects. An interaction term between time and randomized group was also included so that possible differences in treatment effect (informational versus usual care and interactive versus usual care) could be assessed at each time point. The model was adjusted for baseline SBP and minimization factors.

Blood pressure thresholds were analyzed with mixed-effect logis-tic regression models, and treatment adherence was analyzed with multiple logistic regression. Secondary outcomes involving categori-cal data were analyzed by use of χ2 tests and generalized linear mod-els adjusted for minimization factors. Other continuous secondary outcomes were analyzed with ANCOVA or nonparametric methods if the normality assumption was not satisfied. A statistical test of inter-action was done to assess whether treatment effect was consistent

across the prespecified subgroups of SBP (<140 or ≥140 mm Hg), age (<55 or ≥55 years), sex (male or female), number of years with hyper-tension (<10 or ≥10 years), presence of ≥1 comorbid conditions, and self-reported adherence at baseline (<80% or ≥80%).24

A detailed statistical analysis plan was completed before the trial database was locked (to prevent any further changes before analysis), and the trial allocation was disclosed.25 A statistical analysis report was prepared in line with Consolidated Standards of Reporting Trial (CONSORT) 2010 statements. No interim analysis was performed.

The content of the information-only and the interactive adherence support interventions was examined in the preparatory work for the trial (see the expanded Methods in the online-only Data Supplement for further details). The 2 interventions were considered to be distinct treatments and therefore did not require adjustment for multiple com-parisons.26–28 All statistical tests were 2 sided, and values of P≤0.05 were considered to indicate statistical significance.26 Statistical analy-ses were performed with STATA version 13.1 (StataCorp LP, College Station, TX) and SAS version 9.3 (SAS Institute, Cary, NC).

The trial was registered with the South African National Clinical Trials Register (SANCTR DOH-27-1212-386) before recruitment began. This registration was subsequently incorporated within the Pan African Trial Register (PACTR201411000724141), and we regis-tered with ClinicalTrials.gov (NCT02019823) at the time of publish-ing the protocol to ensure that details were widely available.

ResultsPatientsBetween June 26, 2012, and November 23, 2012, we assessed 2558 patients for eligibility, of whom 1372 were randomly allocated to information-only SMS text messages (n=457), interactive SMS text messages (n=458), and usual care (n=457). Figure 1 summarizes recruitment and follow-up of participants. Attrition rates did not differ significantly between groups, and those randomized were broadly similar to those screened but not randomized, although more were black (Table III in the online-only Data Supplement).

Table 1 summarizes the baseline characteristics of partici-pants. Mean age was 54.3 years (SD, 11.5 years), and 28% had at least 10 years of hypertension. More than half of the patients had a body mass index of at least 30 kg/m2. Other baseline characteristics were similar across the 3 groups. Nearly all the participants owned their own phone (Table IV in the online-only Data Supplement). Overall, 176 patients (12.8%) did not have an SBP measurement at 12 months. Not having SBP data at 12 months was associated with being female (P=0.03), hav-ing a body mass index <30 kg/m2 (P=0.002), or having hyper-tension for <10 years at enrollment (P=0.002). We sent 40 333 SMS text messages to participants in the information-only message group, 41 450 to those in the interactive message group, and 8277 to those receiving usual care. Of the mes-sages sent, 5.5% had a “failed delivery” response. In addition, 3477 messages were not sent as planned because of techni-cal errors. A total of 230 participants (50.2%) allocated to the interactive adherence support group responded to a message at some point in the trial; in total, 630 reply messages were sent by participants. There were 1231 visits by participants in the interactive group, 1109 by those in the information-only group, and 1093 by participants in the usual care group. One additional blood pressure–lowering medication was started by 44% of trial participants, and for this group, the median number of changes made was 2 (quartiles 1 and 3, 1 and 3). There were no differences between groups in the proportion of

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patients having medication changes (usual care, 43.6%; infor-mation only, 46.8%; and interactive, 44.0%).

Primary OutcomePrimary outcome data were available for 1256 participants (92%). Table 2 summarizes change in mean SBP, which decreased from baseline to 12 months for all groups. The mean adjusted difference in change for the information-only message group compared with the usual care group was −2.2 mm Hg (95% confidence interval [CI], −4.4 to −0.04, P=0.046) and for the interactive message group compared with the usual

care group was −1.6 mm Hg (95% CI, −3.7 to 0.6, P=0.16). A post hoc sensitivity analysis was carried out, excluding the 6-month measure of SBP and including body mass index as a covariate. Results were consistent with the prespecified pri-mary intention-to-treat analysis (Table V in the online-only Data Supplement).

Secondary OutcomesThe adjusted odds ratios for participants achieving a con-trolled blood pressure defined as a blood pressure <140/90 mm Hg at 12 months were 1.4 (95% CI, 1.0–1.9; P=0.04) and

Figure 1. Trial profile. BP indicates blood pressure; and SMS, short message system.

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1.4 (95% CI, 1.0–1.9; P=0.04) for information-only messages and interactive messages, respectively, compared with usual care (Table 3).

Adherence data were available for 1157 participants (86%). The overall number of participants who had at least 80% of proportion of days of medication covered for blood pressure–lowering medication for the 12-month period was 248 (62.8%) for the information-only message group, 225 (59.7%) for the interactive message group, and 190 (49.4%) for the usual care group (informative messages versus usual care,

P<0.001; interactive messages versus usual care, P=0.002; Table 3). The adjusted odds ratio for improved availability of dispensed medicine was 1.86 (95% CI, 1.39–2.49; P<0.0001) for information-only messaging compared with usual care and 1.60 (95% CI, 1.20–2.16; P=0.002) for interactive messaging compared with usual care.

EuroQol Group 5-Dimension Self-Report Questionnaire scores, attendance at clinic appointments, retention in clinical care, treatment and clinic satisfaction, hypertension knowl-edge, self-reported adherence, hospital admissions, and dif-ferences in medication changes did not differ between groups (Table 3).

Seventeen patients died (usual care group, n=3; infor-mation-only messages group, n=7; and interactive messages group, n=7) during the 12-month follow-up, but we recorded no other serious events (Table VI in the online-only Data Supplement).

Subgroup Analysis of Primary DataFigure 2 shows the results of prespecified subgroup analysis of the primary outcome (SBP). There was no statistically signifi-cant heterogeneity in the treatment effects, and there was an indication that active interventions were more effective among older patients (≥55 years of age), patients in better control at baseline (<140 mm Hg), and among those with a shorter dura-tion of hypertension (<10 years).

DiscussionSummary of Trial FindingsThis trial provides evidence that support delivered via SMS text messages could improve the collection of medicines and may have a small impact on blood pressure compared with usual care in a general outpatient population of adults with high blood pressure. There was no evidence of differences in intervention effectiveness between men and women, younger and older patients, and patients with and without comorbid conditions.

Strengths and LimitationsThis randomized trial of a behavioral intervention delivered via SMS text message was carried out in a low-resource set-ting and was designed to test for the impact of the intervention on prespecified measurable intermediate variables that are linked to important clinical outcomes.29–31

We prepared a detailed statistical analysis plan and speci-fied in advance adjustment by covariates to ensure transparent analysis procedures.25 We have provided detailed descriptions of the intervention and its delivery, in line with recent report-ing guidelines,16 that will enable comparison with other SMS text messaging–based systems and support development of new interventions.

The system for delivering the text messages was innova-tive, combining low-cost technology, open-source software, and interoperability with external data sources, including the Department of Health of the Western Cape appointment data.

The trial had a number of limitations inherent in its design. The provision of free medication and recommendations for

Table 1. Baseline Characteristics

Usual Care (n=457)

Information Only (n=457)

Interactive (n=458)

Age, y* 54.7 (11.6) 53.9 (11.2) 54.2 (11.6)

Male sex, n (%)* 126 (28) 126 (28) 127 (28)

Race or ethnic group, n (%)

Black 264 (58) 257 (56) 269 (59)

Other† 193 (42) 200 (44) 189 (41)

Duration of hypertension, n (%)*

<10 y 327 (72) 331 (72) 330 (72)

≥10 y 130 (28) 126 (28) 128 (28)

Smoking status, n (%)

Nonsmoker 332 (73) 335 (73) 341 (75)

Current smoker 99 (22) 94 (21) 88 (19)

Ex-smoker 26 (5) 27 (6) 29 (6)

Missing 0 1 (0.2) 0

Weight, kg 84.0 (18.9) 83.0 (18.5) 82.8 (19.8)

Body mass index, kg/m2 33.2 (7.7) 32.6 (7.6) 32.5 (7.5)

Blood pressure, mm Hg

Systolic* 135.4 (17.6) 135.1 (16.9) 135.6 (18.1)

Diastolic 83.6 (12.4) 83.1 (11.9) 83.6 (12.0)

Irregular clinic attendance, n (%)‡

288 (63) 288 (63) 290 (63)

Highest level of education at school, n (%)

No schooling 10 (2.2) 8 (2.2) 4 (0.9)

Some primary school 132 (28.9) 155 (28.9) 154 (33.6)

Some high school 261 (57.1) 229 (57.1) 249 (54.4)

Completed high school 54 (11.8) 64 (11.8) 51 (11.1)

Not reported 0 (0) 1 (0.2) 0 (0)

Type of house, n (%)

Brick/cinderblock 378 (82.7) 377 (82.5) 382 (83.4)

Wood/corrugated Iron 73 (16.0) 75 (16.4) 73 (15.9)

Cardboard/plastic 1 (0.2) 0 (0) 0 (0)

Other 5 (1.1) 4 (0.9) 3 (0.7)

Not reported 0 (0) 1 (0.2) 0 (0)

Data are mean (SD) when appropriate.*Minimization variables.†Race was self-reported. Other categories include white, colored, Indian,

other, and prefer not to say.‡Appointment attendance was categorized as follows: regular, attended

the last 4 clinic appointments; irregular, missed at least 1 appointment; and unknown, no previous data on clinic appointments were found.

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regular follow-up at the clinic may have reduced some supply-side barriers to nonadherence, although up to half the partici-pants were not collecting regular treatment. The trial was not powered to identify the observed difference in SBP observed between groups, although our sample size calculation was based on the effect sizes found in published trials of other behavioral interventions to support adherence to treatments for high blood pressure.32 In addition, the measure of adher-ence used reflects only dispensing in the clinic, not the act of taking medication.

Targeting a group of people diagnosed with hyperten-sion rather than those with a diagnosis of poorly controlled pressure may have also limited the extent to which improve-ments in blood pressure were possible. However, we could not reliably predict those with poor control as a result of poor

adherence, nor could we identify when nonadherence might take place in a previously adherent patient. Our decision not to target nonadherent patients was informed by formative work in which we identified the possibility that nonadherence could start at any time and by patient feedback that SMS messages targeted at people who were nonadherent might reduce their acceptability.

Comparisons With Other LiteratureThis is the first study to report a small impact on objectively measured blood pressure using support via text messaging without additional blood pressure monitoring33 and without healthcare providers contacting nonadherent patients.30 We found no evidence that an interactive intervention delivered with the same frequency as an information-only intervention

Table 2. Mean SBP Outcomes (Including Primary Outcome)

UC IO INDifference in Mean Change

(95% CI),* IO vs UC P Value*Difference in Mean Change

(95% CI),* IN vs UC P Value*

Baseline mean SBP, mm Hg 135.4 (17.6) 135.1 (16.9) 135.6 (18.1) … …

6-mo Mean SBP, mm Hg 128.9 (17.1) 130.1 (16.6) 128.2 (17.5) 0.3 (−2.5 to 3.1) 0.82 −0.9 (−3.7 to 1.9)* 0.53

12-mo Mean SBP, mm Hg† 134.3 (17.3) 132.1 (16.6) 132.7 (17.5) −2.2 (−4.4 to −0.04) 0.046 −1.6 (−3.7 to 0.62)* 0.16

Data are mean (SD) SBP. Numbers of participants providing data at each time point are as follows: baseline: UC, n=457; IO, n=457; and IN, n=458; 6 months: UC, n=213; IO, n=245; and IN, n=241; and 1 year: UC, n=396; IO, n=406; and IN, n=394. CI indicates confidence interval; IN, interactive; IO, information only; SBP, systolic blood pressure; and UC, usual care.

*Adjusted for baseline SBP, age, sex, number of years with hypertension, and appointment attendance.†Primary outcome.

Table 3. Secondary Outcomes at 1 Year of Follow-Up

UC(n=385)

IO(n=395)

IN(n=377)

IO vs UC*(95% CI) P Value*

IN vs UC*(95% CI) P Value*

Proportion blood pressures <140/90 mm Hg, n (%)†

396 (58) 406 (65) 394 (65) 1.42 (1.03 to 1.95)‡ 0.033 1.41 (1.02 to 1.95) 0.038

PDC by dispensed medicine, median (quartiles 1–3), %§

79.2 (64.6 to 91.4)

83.3 (69.3 to 91.7)

83.3 (66.7 to 91.7)

5.2 (1.5 to 8.9) 0.006 3.8 (0.03 to 7.6)

0.048

PDC ≥80%§ n (%) 248 (63) 225 (60) 1.86 (1.39 to 2.49) <0.001 1.60 (1.20 to 2.16)

0.002

Euro-Qol 5-Dimension Index, median (quartiles 1–3)§

0.82 (0.73 to 0.90)

0.83 (0.74 to 0.90)

0.81 (0.73 to 0.90)

0.01 (−0.01 to 0.02)

0.50 0.003 (−0.02 to 0.02)

0.73

Retention in clinical care, n (%)† 383 (84) 379 (83) 378 (83) 0.93 (0.66 to 1.32)¶ 0.69 0.90 (0.64 to 1.28)¶ 0.567

Satisfaction with clinic services, median (quartiles 1–3), %‖

28 (25 to 31) 28 (25 to 31) 27 (25 to 31) −0.2 (−1.4 to 0.9)# 0.74 −0.1 (−1.3 to 1.0)# 0.80

Satisfaction with treatment, median (quartiles 1–3), %‖

20 (17 to 20) 20 (18 to 20) 20 (17 to 20) 0 (−0.3 to 0.3)# >0.99 0 (−0.3 to 0.3)# >0.99

Self-reported adherence, median (quartiles 1–3)‖

10 (9 to 10) 10 (9 to 10) 10 (9 to 10) 0.04 (−0.1 to 0.2)# 0.70 0.02 (−0.2 to 0.2)# 0.80

Hospital admissions, n (%)‖ 34 (7) 26 (6) 64 (14) 0.73 (0.43 to 1.24)** 0.24** 0.94 (0.57 to 1.55)** 0.81**

Medication changes, n (%)§ 168 (44) 185 (47) 166 (44) 1.18 (0.88 to 1.57)¶ 0.26 1.04 (0.78 to 1.40)¶ 0.78

Data are n (%) or median (interquartile range) unless indicated otherwise. CI indicates confidence interval; IN, interactive; IO, information only; PDC, proportion of days covered; and UC, usual care.

*Adjusted comparisons for IO versus UC and IN versus UC unless specified.†For blood pressure proportion in control and retention in clinical care data: UC, n=457; IO, n=457; and IN, 458.‡Blood pressure comparisons are adjusted odds ratios.§For dispensing data: UC, n=385; IO, n=395; and IN, n=377.‖For satisfaction, self-reported adherence, and hospital admissions: UC, n=395; IO, n=405; and IN, n=390.¶CIs were derived with multiple logistic regression.#CIs derived with quantile regression.**Without any adjustment of baseline covariates because numbers in cells were small.

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598 Circulation February 9, 2016

had a greater effect on adherence or blood pressure, in contrast to findings from other mobile phone–based interventions.34,35 This might be explained by the older average age of partici-pants in this trial compared with other mobile phone–based studies and could indicate either an age-based or experience-based difference in how people make use of such technology.

Both trial interventions in StAR were delivered with simi-lar fidelity to the trial protocol. Slightly more SMS text mes-sages were sent in the interactive intervention group compared with the information-only group because of a small number of additional follow-up messages. Fifty percent of participants allocated to the interactive intervention responded, whereas in comparison, 38.5% of participants in a smoking cessation trial sent unprompted SMS texts requesting support.36 In a trial of weekly interactive SMS text messages to support treatment adherence among HIV-infected people initiating antiretroviral treatment, 68% of participants responded, with nonresponders receiving a phone call from a healthcare worker.8

The effect size observed on SBP was smaller than antici-pated, particularly because the impact on treatment adherence was similar to that reported by others.9,35 However, those taking additional medication and achieving a lower blood pressure through better adherence may have been only a small propor-tion of participants. A smaller standard deviation for SBP, the greater follow-up of participants than anticipated, and the use of a mixed model for analysis all may have contributed to the detection of a difference smaller than originally anticipated.

Results from a recent systematic review of interventions delivered via SMS text message to support adherence to anti-retroviral therapy suggest that the dose-response relation-ship for SMS text message frequency, if it exists, may not be linear, although counterintuitively, daily SMS text messages were less effective than weekly messages.35 More research is

needed to identify the optimal frequency for SMS text mes-sages to support treatment adherence.

The decrease in blood pressure observed in all participants at 6 months may be attributable to seasonal variation in blood pressure.37 However, this finding should be interpreted with caution because 6-month data were intended to supplement the multilevel modeling of the primary outcome when available and were collected for only a small proportion of participants.

Clinical Interpretation and Research ImplicationsHigh blood pressure is the leading risk factor for global dis-ease burden, and even modest reductions in blood pressure are important and would reduce the risk of associated morbid-ity and premature mortality.1,2 Although availability of medi-cines and access to care remain important structural barriers to adherence in settings where health care and medicines are freely available (including many low- and middle-income countries such as South Africa), a substantial burden of car-diovascular disease may be attributable to suboptimal adher-ence to blood pressure–lowering treatments.

The difference in blood pressure observed in this trial was similar to that of intensive face-to-face behavioral counsel-ing in which a 1–mm Hg difference between intervention and control was observed,38 and the difference in adherence was similar to other adherence support interventions delivered via SMS text messages.39,40 Pooled results from a systematic review of the literature suggest that the relative risk of devel-opment of cardiovascular disease for those with good versus poor (<80%) adherence to blood pressure–lowering medica-tion is 0.81 (95% CI, 0.76–0.86) and for all-cause mortality is 0.71 (95% CI, 0.64–0.78) with an estimated absolute risk difference for any cardiovascular disease associated with poor medication adherence of 13 cases per 100 000 individuals

Figure 2. Subgroup analysis of prespecified subgroups of the primary outcome (systolic blood pressure) for information-only vs usual care (A) and interactive vs usual care (B).

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Bobrow et al SMS Text Adherence Support for High Blood Pressure 599

per year.5 Although not reported here, we think that the costs of delivering messages via an automated SMS text mes-sages at scale are likely to be low compared with commu-nity based face-to-face interventions or training programs for clinicians.8,41,42

ConclusionsThis trial has demonstrated that a behavioral intervention to support adherence to blood pressure treatment delivered via SMS text message can improve adherence and may modestly decrease blood pressure at 12 months. The delivery of pre-defined messages can be achieved by an automated system consistently and without the need for additional training pro-grams for clinical staff. The optimal frequency of the different categories of text messages; the incremental costs of modi-fying messages so that they remain effective; and the wider implementation of these messages in different communities, for different long-term conditions, and for patients with mul-tiple conditions need further study.

AcknowledgmentsWe are grateful to the patients, healthcare workers, pharmacists, clinic administrative staff, and field staff under Sister Carmen Delport for taking part in this trial. We also are grateful to the Department of Health of the Western Cape for support of the trial and access to routinely collected administrative data.

Sources of Funding This trial is supported by the Oxford Centre of Excellence in Medical Engineering funded by the Wellcome Trust and the Engineering and Physical Sciences Research Council. Dr Farmer is a senior NIHR investigator, and Drs Farmer and Tarassenko are supported by fund-ing from the NIHR Oxford Biomedical Research Center. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

DisclosuresNone.

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doi: 10.1007/s10198-012-0424-5.

CLINICAL PERSPECTIvEThere is some evidence that clinical outcomes for the treatment of long-term conditions can be improved through interven-tions targeting adherence behavior. This has been achieved in a small number of clinical trials for people with high blood pressure, but successful strategies can be costly, for example, through case management and pharmacy-based education. These approaches may not be practical in a low-resource setting. Some studies report that mobile phone messaging interven-tions may offer benefit through supporting self-management and have potential to support lifestyle change, for example, in supporting smoking cessation. However, randomized trials of the effectiveness of mobile phone messaging in the manage-ment of people with high blood pressure are few, often focused on high-risk groups such as stroke survivors and renal trans-plant recipients, with only 1 small trial in the general population. This randomized, clinical trial is the first to show that there may be a modest benefit from improved adherence to medication regimens and reduction in blood pressure compared with usual care from a targeted mobile phone messaging intervention used to support people treated for high blood pressure. In addition, this intervention was delivered in a setting where providing health care is challenging. The extent of blood pressure lowering is similar to that observed in other community studies aimed at improving blood pressure management. Delivering an automated behavioral intervention to people treated for high blood pressure via mobile phones is acceptable to recipients and can be carried out at a wide scale.

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Pressure (SMS-Text Adherence Support [StAR]): A Single-Blind, Randomized TrialMobile Phone Text Messages to Support Treatment Adherence in Adults With High Blood

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SUPPLEMENTAL MATERIAL

Supplementary Table 1: Behavior change techniques used in the StAR SMS text-messaging intervention.

Behavior change technique cluster*

Text message content† Type of message‡

Repetition and substitution

Habit formation Taking your medicine at the same time every day can help you remember to take your pills regularly.

Weekly

Behavior substitution Please remember, if you can't make your MEDICINES TIME&DATE, send someone you trust to pick-up your pills. We need your clinic card and their identification document.

Behavioral rehearsal/practice Planning ahead (counting out tomorrow’s pills today) can help you remember to take your pills.

Weekly

Generalization of a target behavior

Your good health is important. Please try to do more exercise. Activities that make you sweat or your heart beat faster are good for you.

Weekly

Natural consequences

Health consequences Please tell us (DR&PHARMACY) if you think your high blood pills are making you feel unwell. Ask us about common side effects of your pills.

Weekly

Salience of consequences Please don’t give yours meds to people who are not prescribed them. Giving other people pills can endanger their health. Ask them to please come to the clinic.

Weekly

Anticipated regret Did you know untreated high blood (when you don't take your pills) puts you at risk for heart disease? Please take your pills as directed.

Weekly

Goals and planning

Action planning Ask someone you trust to help you remember to take your medicine as directed.

Weekly

Problem solving Please remember to come back to clinic if you run out of medicine before your next date. You can come even if it is not your date.

Weekly

Commitment Please remember your high blood is with you always. Work with [CLINIC NAME] to stay healthy. Keep your clinic dates & take your medicine as directed.

Weekly

Goal setting (outcome) Please remember your next MEDICINE PICK-UP DATE is on [DAY][DD/MM/YY] at [00:00].

48 hours prior to scheduled appointment

Behavioral contract Please remember your high blood can’t be cured. To keep healthy Please keep on with your pills, come on your booked clinic dates, exercise & eat healthy food

Weekly

Review of behavior goals Thanks for picking up your meds. Keeping on your pills & attending on your correct dates helps us serve you better.

48 hours post scheduled appointment

Social support

Practical Please be sure to tell the PHARMACY if you need to go away. We will give you a letter & extra pills so you won't run out.

Weekly

General Work with us to stay healthy. Learn about your condition & how to manage it. For more info ask us.

Weekly

Emotional You are an important member of your community. Please keep trying with a healthy lifestyle. Please try to do more exercise.

Weekly

* Michie et al (2008)

†All text messages were signed off by a named health care provider

‡ Participants received one message per week, either a reminder to attend an up-coming appointment (48-hours prior to scheduled appointment) or a message selected-at-random from the message library.

Participants selected the time of day at which the message was sent, at trial recruitment

Supplementary Table 2: Checklist for development of the SMS-text Adherence suppoRt (StAR) intervention

1. Brief name Control Group Information-only SMS intervention Interactive SMS intervention

2. Rationale or theory

Mobile phones are contextual tools which could deliver an ecological momentary intervention [1]. We used SMS text-messages (text’s) because of their widespread availability. We drew on an integrated theory of behaviour change,[2] to guide message development alongside evidence-based behaviour change techniques (BCT)[3]. Messages were made available in participants’ preferred language. As the relative effect on clinical outcomes of an informational versus interactive system of SMS-text messages was unclear from the literature, we included two intervention arms, one with information only SMS-text’s, and one that included an interactive component.

Infrequent non-health related SMS-texts sent to all participants with the aim of: 1. Maintaining participant interest in the trial. 2. Making it less clear who was getting which intervention 3. Excluding receipt of “any SMS” as a factor in effecting health-related behaviour in comparison with

usual care

Information-only SMS intervention

1. Timely, relevant, personalised information designed to address common challenges to adherence

2. Content focused on BCT of goals and planning, repetition and substitution, social support, natural consequences

3. Unidirectional SMS-text messages

4. Messages designed to be polite, direct, signed off by named provider

Interactive SMS intervention

1. Timely, relevant, personalised information designed to address common challenges to adherence

2. Content focused on BCT of goals and planning, repetition and substitution, social support, natural consequences

3. Bidirectional SMS-text messages

4. Messages designed to be polite, direct, signed off by named provider

3. Materials Additional health information leaflet in preferred language provided at baseline-trial visit

4.

Procedures Delivery of text messages

1. Language and timing of messages selected by participant

2. Welcome SMS-text

3. “Happy birthday” SMS-text

4. Non-health related SMS-

text message sent at 6-weekly intervals (randomly selected)

1. Language and timing of messages selected by participant

2. Welcome SMS-text

3. “Happy birthday” SMS-text

4. Non-health related SMS-text message sent at 6-weekly intervals (randomly selected)

5. Weekly SMS-text message,

randomly selected from library (with rule that ensured messages were not repeated)

6. SMS-text message reminder

to attend scheduled clinic appointment 48 hrs prior to date

7. SMS-text message to either

thank participant for attending appointment or alert participants about a missed appointment 48 hrs post date

1. Language and timing of messages selected by participant

2. Welcome SMS-text

3. “Happy birthday” SMS-text

4. Non-health related SMS-

text message sent at 6-weekly intervals (randomly selected)

5. Interactive-SMS to check

timing and language of messages was acceptable (automated system to make change if required)

6. Weekly SMS-text

message, randomly selected from library (with rule that ensured messages were not repeated)

7. Interactive-SMS to remind

participant of up-coming appointment and offer to reschedule if date no-longer convenient (48 hrs prior to appointment date)

8. Interactive-SMS thanking

participant for attending appointment or offer to reschedule a missed

appointment 48 hrs post date)

9. Interactive-SMS to trouble shoot common problems at the health facility (long queues, lost folders)

5. Intervention provider Automated SMS-text delivery platform using open-source software badged from clinical facility based on local smart-phones linked to a secure server

6. Modes of delivery Intervention delivered via 160 character SMS text-message sent to individual participant’s own handset

7. Location where intervention occurred Outside of health care facility, where ever participant and their phone were located (real world)

8. Number of times intervention was delivered over what time period

SMS-text message sent about once every 6 weeks for 12-months

SMS-text message sent weekly for 12-months

SMS-text message sent weekly for 12-months (with follow-up messages generated through user initiated dialogue)

9.

What, why, when, how intervention was personalised or adapted

1. Language and timing of

messages selected by participant

2. Date of birth recorded for birthday message

1. Language and timing of

messages selected by participant

2. Date of birth recorded for birthday message

3. Personalised timing of

appointment reminders based on prospectively routinely collected computerised appointment data

1. Language and timing of

messages selected by participant

2. Date of birth recorded for birthday message

3. Interactive-SMS to check

timing and language of messages was acceptable (if not automated SMS-dialogue to change either language or timing)

4. Personalised timing of

appointment reminders based on prospectively routinely collected computerised appointment data

5. Regular interactive-SMS to enable rescheduling of

up-coming or missed appointments, and to troubleshoot common challenges at the health facility

10. Modifications during the trial Nil Nil Nil

11. Planned intervention delivery

SMS-text messages were sent using an automated system independent of trial and clinical staff. Participants were told that not everyone would be receiving the exact same messages. Participants were also asked not to share the SMS text-messages with others. Intervention fidelity was checked by confirming receipt at least of an initial “Welcome” SMS text-message for all enrolled trial participants prior to randomisation. Message delivery reports were monitored throughout the trial to check the intervention was being delivered as planned. Messages not delivered (for example, network unavailable) were re-sent up to three times.

12. Actual intervention delivery 8,277 individual SMS-text messages over 12-month period (457 participants)

40,333 individual SMS-text messages over 12-month period (458 participants)

41,450 individual SMS-text messages over 12-month period (458 participants)

References

[1] K. E. Heron and J. M. Smyth, “Ecological momentary interventions: Incorporating mobile technology into psychosocial and health behaviour treatments,” Br J Health Psychol, vol. 15, no. 1, pp. 1–39, Jan. 2011.

[2] H. de Vries, A. Mudde, I. Leijs, A. Charlton, E. Vartiainen, G. Buijs, M. P. Clemente, H. Storm, A. González Navarro, M. Nebot, T. Prins, and S. Kremers, “The European Smoking Prevention Framework Approach (EFSA): an example of integral prevention.,” Health Educ.Res., vol. 18, no. 5, pp. 611–626, Oct. 2003.

[3] C. Abraham and S. Michie, “A taxonomy of behavior change techniques used in interventions.,” Health Psychol., vol. 27, no. 3, pp. 379–387, May 2008.

Supplementary Table 3: Comparison of randomized and non-randomized patients

Variables Randomised

(n=1372)

Not Randomised

(n=1186)

Age (years), mean (SD) [n=2534] 54.4 (11.5) 60.6 (12.9)

Sex:

Male, n (%) 379 (27.6) 343 (28.9)

Ethnicity:

Black, n (%) 790 (57.6) 378 (32.7)

Colored, n (%) 565 (41.2) 762 (65.9)

Other, n (%) 17 (1.2) 17 (1.5)

Weight (kg), mean (SD) [n=2491] 83.3 (19.1) 77.0 (18.6)

BMI, mean (SD) [n=2489] 32.7 (7.6) 30.5 (7.2)

Systolic BP (mmHg), mean (SD) [n=2486] 135.4 (17.6) 138.8 (21.4)

Supplementary table 4: Access to Cell-phone technology by randomized group

Usual care Information only Interactive n (%) n (%) n (%) n= 457 n=457 n=458

Have their own cell-phone 435 (95.2) 432 (94.5) 432 (94.3) Spouse/Partner 6 (1.3) 9 (2.0) 7 (1.5) Other family member 16 (3.5) 15 (3.3) 19 (4.1)

Missing data Usual care 0; Information only 1, Interactive 0.

Supplementary Table 5: Sensitivity analysis of systolic blood pressure at 12 months

Difference in P-Value* Difference in P-Value*

mean change (95% CI)* mean change (95% CI)*

IO vs. UC IN vs. UC

Mixed effects model adjusting -2.1 (-4.3 to 0.04) 0.054 -1.5 (-3.7 to 0.67) 0.18

ANCOVA -2.2 (-4.3 to -0.01) 0.049 -1.6 (-3.8 to 0.60) 0.16

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UC Usual Care; IO Information Only: IN Interactive.

*Adjusted for baseline systolic blood pressure, age, gender, number of years with hypertension, appointment attendance, body mass

index

Numbers of participants providing data at each time-point: baseline UC n=457, IO n=457, IN n=458; six months UC n=213, IO=245, IN

n=241; one year UC n=396, IO n=406, IN n=394

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Supplementary Table 6: Cause of death in trial participants

Control Interactive Information Total

Unknown cause 1 1 1 3

CCF 0 2 0 2

CKD 0 0 1 1

COPD 0 1 0 1

Cancer 0 2 2 4

Ischemic heart disease 0 0 2 2

LRTI 0 0 1 1

Pulmonary TB 2 0 0 2

HIV-related 0 1 0 1

Total 3 7 7 17

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The StAR trial Collaboration

Writing committee: Kirsten Bobrow, Andrew J Farmer, David Springer,

Milensu Shanyinde, Ly-Mee Yu, Thomas Brennan, Brian Rayner, Mosedi

Namane, Krisela Steyn, Lionel Tarassenko, Naomi Levitt.

Trial steering committee: Carl Lombard (Chair), Lionel Tarassenko, Karen

Sliwa, Bob Mash, Tracey Naledi, Naomi Levitt and Andrew Farmer.

Trial management committee: Andrew Farmer, Kirsten Bobrow, Naomi Levitt,

Brian Rayner, Krisela Steyn,

Coordinating Centre Oxford: Andrew Farmer, Ly-Mee Yu, Milensu Shanyinde,

David Judge; Institute of Biomedical Engineering: Lionel Tarassenko, David

Springer.

Coordinating Centre Cape Town: Kirsten Bobrow, Carmen Delport, Carmelita

Sylvester, Susan Botha, Chantel Stuart.

Intervention Development: Thomas Brennan, Nomazizi Cishe, Ntobeko

N’wagi, David Springer.

Trial research assistants: Liezel Fisher, Melissa Paulse, Nicolette Gertse,

Theresa Louw, Ntombi Ngabom, Nomfuneko Konzapi, Desmond Raqa,

Nombulelo Ralarala, Luyanda Sebe, Malibongwe Majola, Morris Manuel,

Maureen Fortune.

Vanguard Clinic staff: Mosedi Namane, Luntu Mbanga, Zameka Sibinda,

Zeenat Yusuf.