This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR mHealth and uHealth, is properly cited. The complete bibliographic information, a link to the original publication on https://mhealth.jmir.org/, as well as this copyright and license information must be included.
Acute coronary syndrome (ACS) is a leading cause of hospital admission in North America. Many patients with ACS experience challenges after discharge that impact their clinical outcomes and psychosocial well-being. SMS text messaging has the potential to provide support to patients during this postdischarge period.
This study pilot tested a 60-day SMS text messaging intervention (Txt2Prevent) for patients with ACS. The primary objective was to compare self-management domains between usual care and usual care plus Txt2Prevent. The secondary objectives were to compare medication adherence, health-related quality of life, self-efficacy, and health care resource use between groups. The third objective was to assess the feasibility of the study protocol and the acceptability of the intervention.
This was a randomized controlled trial with blinding of outcome assessors. We recruited 76 patients with ACS from St. Paul’s Hospital in Vancouver, Canada, and randomized them to 1 of 2 groups within 7 days of discharge. The Txt2Prevent program included automated 1-way SMS text messages about follow-up care, self-management, and healthy living. Data were collected during the index admission and at 60 days after randomization. The primary outcome was measured with the Health Education Impact Questionnaire (heiQ). Other outcomes included the EQ-5D-5L, EQ-5D-5L Visual Analog Scale, a modified Sullivan Cardiac Self-Efficacy Scale, and Morisky Medication Adherence Scale scores, and self-reported health care resource use. Analyses of covariance were used to test the effect of group assignment on follow-up scores (controlling for baseline) and were considered exploratory in nature. Feasibility was assessed with descriptive characteristics of the study protocol. Acceptability was assessed with 2 survey questions and semistructured interviews.
There were no statistically significant differences between the groups for the heiQ domains (adjusted mean difference [Txt2Prevent minus usual care] for each domain—Health-directed activity: –0.13, 95% CI –0.39 to 0.13,
The Txt2Prevent study was feasible to implement; however, although exploratory, there were no differences between the 2 groups in adjusted analyses except for 1 self-efficacy domain. As the intervention appeared acceptable, there is potential in using SMS text messages in this context. The design of the intervention may need to be reconsidered to have more impact on outcome measures.
ClinicalTrials.gov NCT02336919; https://clinicaltrials.gov/ct2/show/NCT02336919
RR2-10.2196/resprot.6968
Acute coronary syndrome (ACS), which includes unstable angina and myocardial infarction, is a leading cause of hospitalization in North America [
Home-based programs, often nurse led, can improve quality of life and reduce readmissions [
The Txt2Prevent study is a mixed method, assessor-blinded, randomized controlled trial with a parallel group design. The study protocol and intervention development have been previously reported [
Patients with a diagnosis of ACS, as identified by clinical staff, were recruited from St. Paul’s Hospital, a tertiary care hospital, in Vancouver, Canada between June 2015 and October 2016. Patients were eligible to participate if they had ACS (unstable angina or any type of myocardial infarction) as their primary admitting diagnosis, had daily access to a phone with SMS text messaging capabilities, were able to provide informed consent, and were able to read and understand English. Exclusion criteria comprised having coronary artery bypass graft surgery as a treatment for the ACS admission, having a prescheduled surgery within the study period, an expectation that the individual would not survive the duration of the study due to non-CVD reasons, being discharged to a long-term care center, or living outside the province of British Columbia. As this was a pilot study, the sample size was based on convenience. We aimed to recruit 76 participants as we previously estimated this was feasible over 6 months of recruitment. All participants provided written informed consent. Ethics and institutional approvals were obtained from Providence Health Care Research Ethics Board and Simon Fraser University’s Office of Research Ethics.
Baseline questionnaires, which included demographic information as well as measures of self-management, health-related quality of life, and cardiac self-efficacy, were administered in-person in the hospital when possible or within 7 days after discharge. Clinical information was gathered from the participant’s medical record.
After participants completed the baseline questionnaires and were discharged from the hospital, they were randomly assigned to either the intervention (Txt2Prevent plus usual care) or usual care. A statistician not associated with the study generated a random allocation schedule, which randomized participants in a 1:1 ratio using variable block sizes, stratified by sex. A research assistant not involved in recruitment or outcome assessment accessed a secure randomization database to obtain allocations for each patient and informed participants of their group assignment.
Participants in the Txt2Prevent group received 48 unique, automated, one-way messages over 60 days following randomization in addition to usual care. An additional 4 messages relating to study administration (eg, indicating the end of the study and requesting participants to inform us if they were readmitted; see SMS text messages sent on days 7, 26, 45, and 60 in
Examples of the SMS text messages in the intervention group (Txt2Prevent).
Topic | Example SMS text message |
Appointment reminders | T2P: See a heart specialist (a cardiologist or internist) within 6 weeks of discharge. If this isn’t set up, call their office, or your family doctor. (Day 15) |
Smoking cessation | T2P: Not smoking is one of the most important things you can do for your health. For quitting resources, check out: http://bit.ly/quitnowbc (Day 8) |
Recovery guidelines | T2P: Resuming sex: A general guide is that if you can go up a flight of stairs without symptoms, it is probably safe to restart sexual activities. (Day 14) |
Psychosocial | T2P: It is common to feel sad or depressed after a heart attack or being in the hospital. If you feel this way for 2+ weeks, contact your doctor. (Day 16) |
Physical activity | T2P: Have you done something physically active today? If you have questions, call the Physical Activity Line at 1-877-725-1149 or talk to your doctor. (Day 21) |
Medication | T2P: Bring a list of your medications to your appointment when you see your doctor. You can get copies from your pharmacist. (Day 9) |
The primary outcome was follow-up scores (controlled for baseline scores) in self-management domains as measured by the Health Education Impact Questionnaire (heiQ; version 3) [
The secondary outcomes were health-related quality of life, cardiac self-efficacy, medication adherence, and health care resource use. Health-related quality of life was measured with the EQ-5D-5L [
Study feasibility was assessed through descriptive statistics on recruitment rates, follow-up rates, questionnaire completion rates, method of questionnaire completion (eg, postal mail, phone), percentage of participants randomized within 7 days, and percentage of participants who completed follow-up within 6 weeks after finishing the 60-day study period. In addition, study staff kept a log of barriers encountered. Acceptability was measured via two 5-level Likert scale survey questions that asked how satisfied participants were with the program (strongly disagree to strongly agree) and whether they thought the program helped them manage their condition. Acceptability was also assessed via 2 questions in semistructured phone interviews—specifically whether they would recommend the program to other patients with ACS and whether they read the SMS text messages. Participants with a range of demographic characteristics who were randomized to the Txt2Prevent group were invited to participate in the semistructured interviews after the 60-day study period. Detailed findings from the interviews, which covered participants’ experiences with the program and gathered feedback on program attributes, will be presented in a separate paper.
Follow-up questionnaires were administered 60 days after randomization primarily via postal mail, except for the health care resource use questions, which were completed over the phone for most participants due to its complex branching. All surveys were administered at baseline and at follow-up, except for the medication adherence scale and health care resource use questionnaire, which were only administered at follow-up.
As this was a pilot study, we undertook similar analyses to what is anticipated for a full trial and considered them exploratory in nature. Descriptive statistics are presented as the mean and SD, or count data with percentages. Analyses were conducted following the intent-to-treat principle. Only complete cases were analyzed. For continuous data from the heiQ, EQ-5D-5L, EQ VAS, and CSE questionnaires, analysis of covariance (ANCOVA) was used to test the effect of group assignment on the follow-up scores when controlling for baseline scores. We then reran the ANCOVA adjusting for age and sex as prespecified covariates as well as previous CVD status for the heiQ, and previous CVD status and marital status for the cardiac self-efficacy, due to their prognostic value [
For count data from the health care resource use questionnaire (eg, number of readmissions), we used negative binomial regression analyses as our data had some overdispersion. For these analyses, we adjusted for age and sex, as prespecified. For binary response data from the health care resource use questionnaire (eg, cardiologist visit within 60 days—yes/no), we used a robust Poisson regression to determine relative risk as our outcomes occurred frequently [
Four hundred patients were assessed for eligibility from June 2015 to October 2016. After excluding those who did not meet inclusion criteria and those who declined to participate, 76 participants were randomized (
The mean age of participants was 60 years (SD 9.3) and 73% (55/75) were male (
CONSORT flow diagram.
Baseline demographics, by group.
Variable | Groupa | |||||||
Txt2Prevent | Usual care | |||||||
|
|
|||||||
|
Age, mean (SD) | 59.5 (9.1) | 61.1 (9.6) | |||||
|
Male, n (%) | 27 (73) | 28 (74) | |||||
|
Married (yes/no), n (%) | 27 (73) | 31 (82) | |||||
|
|
|
|
|||||
|
|
Census metropolitan area (100,000+ urban core) [ |
13 (35) | 21 (55) | ||||
|
|
Census agglomeration (10,000-99,999 urban core) [ |
18 (49) | 8 (21) | ||||
|
|
Rural [ |
6 (16) | 9 (24) | ||||
|
Greater than high-school education (yes/no), n (%) | 23 (62) | 25 (66) | |||||
|
Employed full-time (yes/no), n (%) | 20 (54) | 17 (45) | |||||
|
|
|
|
|||||
|
|
Less than Can $29,999a | 6/33 (18) | 7/36 (19) | ||||
|
|
Can $30,000 to Can $69,999 | 9/33 (27) | 7/36 (19) | ||||
|
|
Can $70,000 to Can $99,999 | 6/33 (18) | 6/36 (17) | ||||
|
|
Can $100,000 or higher | 12/33 (36) | 16/36 (44) | ||||
|
|
|||||||
|
At least daily cell use | 26/36 (72) | 34/38 (89) | |||||
|
Very or completely confident using a cell phone | 18/33 (55) | 26/37 (70) | |||||
|
Own a smartphone | 34/37 (92) | 33/37 (89) | |||||
|
|
|||||||
|
Hypertension | 25 (68) | 19 (50) | |||||
|
Dyslipidemia | 18 (49) | 12 (32) | |||||
|
Diabetes (type 1 or type 2) | 14 (38) | 7 (18) | |||||
|
Previous any type of cardiovascular disease | 16 (43) | 16 (42) | |||||
|
|
|||||||
|
Days in hospital | 5.1 (3.0) | 5.2 (4.2) | |||||
|
|
|
|
|||||
|
|
Non-ST-segment elevation acute coronary syndrome | 10 (27) | 18 (47) | ||||
|
|
ST-segment elevation myocardial infarction | 22 (59) | 17 (45) | ||||
|
|
Other | 5 (14) | 3 (8) | ||||
|
Revascularization, n (%) | 29 (78) | 33/37 (89) | |||||
|
Current/quit within 6-month smoker, n (%) | 8 (22) | 8/37 (22) | |||||
|
|
|||||||
|
Acetylsalicylic acid | 33/36 (92) | 36/37 (97) | |||||
|
Ticagrelor or clopidogrel | 31/36 (86) | 36/37 (97) | |||||
|
Statin | 33/36 (92) | 33/37 (89) | |||||
|
Beta blocker | 29/36 (81) | 33/37 (89) | |||||
|
Angiotensin-converting-enzyme inhibitor or angiotensin II receptor blocker | 29/36 (81) | 32/37 (86) |
an=37 and =38 for the Txt2Prevent and Usual care groups unless stated otherwise.
bCan $1 = US $0.81.
Baseline questionnaire scores, by group.
Baseline variables, mean (SD) | Group | ||||
Txt2Prevent (n=37) | Usual care (n=38) | ||||
|
|
|
|||
|
Health-directed activity | 2.93 (0.80) | 2.93 (0.78) | ||
|
Positive and active engagement in life | 3.13 (0.53) | 3.27 (0.48) | ||
|
Emotional distress | 2.25 (0.68) | 2.02 (0.60) | ||
|
Self-monitoring and insight | 3.19 (0.89) | 3.08 (0.59) | ||
|
Constructive attitudes and approaches | 3.17 (0.51) | 3.35 (0.46) | ||
|
Skill technique and acquisition | 3.02 (0.34) | 3.09 (0.53) | ||
|
Social integration and support | 3.11 (0.49) | 3.30 (0.41) | ||
|
Health service navigation | 3.08 (0.47) | 3.27 (0.47) | ||
EQ-5D-5L | 0.833 (0.119) | 0.849 (0.109) | |||
EQ-5D-5L Visual Analog Scale (EQ VAS) | 67.00 (19.00) | 68.00 (17.00) | |||
|
|
|
|||
|
Symptoms | 3.14 (0.63) | 3.25 (0.52) | ||
|
Function | 2.85 (0.91) | 2.91 (0.83) | ||
|
Total | 3.02 (0.61) | 3.10 (0.57) | ||
|
Total plus | 2.95 (0.58) | 3.02 (0.54) |
There were no statistically significant differences between groups for the heiQ scores in either the unadjusted (
Adjusted 60-day Health Education Impact Questionnaire (heiQ) scores, by group.a
Outcome | Group | Adjusted mean difference (95% CI) | Effect size (Cohen |
|||
Txt2Prevent (n=32), adjusted mean (95% CI) | Usual care (n=36), adjusted mean (95% CI) | |||||
|
||||||
|
Health-directed activityc | 3.02 (2.82 to 3.21) | 3.15 (2.96 to 3.35) | –0.13 (–0.39 to 0.13) | .31 | –0.15 |
|
Positive and active engagement in life | 3.10 (2.93 to 3.26) | 3.06 (2.91 to 3.22) | 0.03 (–0.19 to 0.25) | .76 | 0.10 |
|
Emotional distress | 2.37 (2.18 to 2.56) | 2.33 (2.15 to 2.51) | 0.04 (–0.22 to 0.29) | .77 | –0.05 |
|
Self-monitoring and insight | 3.08 (2.94 to 3.23) | 3.22 (3.09 to 3.36) | –0.14 (–0.33 to 0.05) | .15 | –0.48 |
|
Constructive attitudes and approaches | 3.09 (2.89 to 3.29) | 3.18 (2.99 to 3.38) | –0.10 (–0.36 to 0.17) | .47 | –0.06 |
|
Skill technique and acquisition | 2.91 (2.73 to 3.08) | 2.86 (2.70 to 3.03) | 0.05 (–0.18 to 0.27) | .69 | 0.14 |
|
Social integration and support | 3.04 (2.87 to 3.21) | 3.17 (3.01 to 3.33) | –0.12 (–0.34 to 0.10) | .27 | –0.04 |
|
Health services navigation | 3.15 (2.97 to 3.33) | 3.19 (3.02 to 3.37) | –0.05 (–0.29 to 0.19) | .69 | 0.15 |
aThe adjusted heiQ model includes baseline scores, age, sex, and previous cardiovascular disease status (yes/no).
bEffect size is Cohen
cIn the usual care group, 35 participants were analyzed for the Health-directed activity domain.
There were no statistically significant differences in EQ-5D-5L health state values (
Adjusted 60-day EQ-5D-5L Visual Analog Scale (EQ VAS), EQ-5D-5L, and Cardiac Self-Efficacy results, by group.a
Outcome | Group | Adjusted mean difference (95% CI) | Adjusted |
Effect size (Cohen |
||||||||||
Txt2Prevent (n=32), adjusted mean (95% CI) | Usual care (n=36), adjusted mean (95% CI) | |||||||||||||
EQ-5D-5L Visual Analog Scale (EQ VAS) | 70.94 (65.91 to 75.98) | 69.68 (64.84 to 74.52) | –1.27 (–5.41 to 7.94) | .71 | 0.10 | |||||||||
EQ-5D-5Lc | 0.82 (0.78 to 0.86) | 0.84 (0.80 to 0.88) | –0.018 (–0.07 to 0.04) | .51 | –0.13 | |||||||||
|
||||||||||||||
|
Control symptoms | 2.49 (2.24 to 2.75) | 2.76 (2.49 to 3.02) | –0.27 (–0.58 to 0.05) | .10 | –0.43 | ||||||||
|
Control symptoms (2 outliers removed)c | 2.57 (2.36 to 2.78) | 2.80 (2.57 to 3.02) | –0.23 (–0.49 to 0.04) | .09 | –0.37 | ||||||||
|
Maintain function | 2.14 (1.84 to 2.45) | 2.52 (2.20 to 2.84) | –0.38 (–0.76 to 0.004) | .05 | –0.46 | ||||||||
|
Maintain function (1 outlier removed)c | 2.23 (1.95 to 2.50) | 2.50 (2.22 to 2.78) | –0.27 (–0.61 to 0.07) | .11 | –0.35 | ||||||||
|
Total | 2.35 (2.09 to 2.60) | 2.66 (2.39 to 2.93) | –0.31 (–0.63 to 0.003) | .05 | –0.55 | ||||||||
|
Total (1 outlier removed)c | 2.42 (2.20 to 2.64) | 2.64 (2.41 to 2.86) | –0.22 (–0.49 to 0.05) | .11 | –0.40 | ||||||||
|
Total plus | 2.28 (2.03 to 2.53) | 2.64 (2.38 to 2.90) | –0.36 (–0.66 to –0.05) | .03 | –0.65 | ||||||||
|
Total plus (1 outlier removed)c | 2.35 (2.14 to 2.57) | 2.62 (2.39 to 2.84) | –0.26 (–0.53 to 0.003) | .05 | –0.51 |
aThe adjusted EQ-5D-5L and EQ VAS models include baseline scores, age, and sex. The adjusted CSE model includes baseline scores, age, sex, marital status, and previous cardiovascular disease status (yes/no).
bEffect size is Cohen
cIn the Txt2Prevent group, 31 participants were analyzed for the EQ-5D-5L questionnaire. Thirty-two participants were analyzed for the remaining outcomes (excluding those with outliers removed). For the 2 outliers in the Control symptoms domain, 1 was from the Txt2Prevent group and 1 from the usual care group. The 1 outlier for the Maintain function, Total, and Total plus was from the Txt2Prevent group.
There were no statistically significant differences in the mean medication adherence scores between the 2 groups (
There were no differences between the groups in either the percentage of participants who visited the hospital or the mean number of visits to the hospital for all-cause or cardiac visits (
Type of and mean hospital visits within 60 days, by group.
Outcome | Groupa | Groupb | |||||||
Txt2Prevent (n=32), adjusted mean visits (95% CI) | Usual care (n=37), adjusted mean visits (95% CI) | Txt2Prevent (n=32), n (%) | Usual care (n=37), n (%) | ||||||
Cardiac emergency department | 0.00 (–) | 0.08 (0.02-0.38) | N/A | 0 (0) | 3 (8) | .24 | |||
All-cause emergency department | 0.20 (0.08-0.48) | 0.33 (0.16-0.66) | .36 | 3 (9) | 9 (24) | .10 | |||
Cardiac hospitalization | 0.13 (0.04-0.37) | 0.12 (0.04-0.34) | .92 | 3 (9) | 3 (8) | 1.00 | |||
All-cause hospitalization | 0.16 (0.06-0.42) | 0.21 (0.09-0.48) | .70 | 4 (13) | 6 (16) | .74 |
aMean visits were analyzed with a negative binomial regression adjusted for age and sex.
bNumber of participants—n (%)—admitted for all-cause emergency department visits was analyzed with chi-square (
Recruitment of the target sample took 17 months (
We had a technical problem with our delivery system 11 months into recruitment where 80 SMS text messages were not delivered for 10 days for 28% (10/36) participants. It is suspected an operating system update caused the error as a server reboot fixed the error. Once we fixed the error, all affected participants resumed the SMS text messages where they left off. In order to keep blinding and consistency in the timing of the outcome measurements, follow-up assessments were still scheduled for 60-days after randomization. Of the 10 affected participants, 2 did not complete follow-up, 5 completed the primary outcome assessment between 60 and 70 days after randomization, and 3 completed follow-up after 70 days. After this technical problem, we implemented more regular system checks by the staff involved in randomization to ensure all SMS text messages were being delivered.
Regarding acceptability, over 93% (29/31 [94%]) of participants in the Txt2Prevent group reported they agreed or strongly agreed that they were satisfied with the program. About 74% (23/31) agreed or strongly agreed that it helped them manage their condition. When asked in semistructured interviews, 17/18 participants said they would recommend the program to other patients with cardiac issues. The participant who said he would not recommend the program stated that his recommendation would depend on whether the person took the time to read the SMS text messages. All but 2 interview participants reported reading every SMS text message, and these reported that while they did read most of the SMS text messages, it was possible they did not read all of them. All interviewed participants said they would be willing to use SMS text messaging again for health purposes.
Study protocol feasibility measures.a
Feasibility measure | Descriptive assessment | |
|
||
|
Months of recruitment | 17 |
|
Number participants randomized per month, mean (range) | 4.5 (0-15) |
|
Ineligible patients, n/N (%) | 223/400 (55.8) |
|
Eligible patients who declined to participate, n/N (%) | 96/172 (55.8) |
|
||
|
Days from discharge to randomization, mean (SD) | 2.1 (2.1) |
|
Participants randomized within 7 days of discharge, n/N (%) | 74/76 (97) |
|
||
|
Completed packaged follow-up questionnaires, n/N (%) | 69/76 (91) |
|
Packaged follow-up questionnaires done by postal mail, n/N (%) | 60/69 (87) |
|
Days after discharge to complete packaged follow-up questionnaires, mean (SD) | 73 (17) |
|
Completed packaged follow-up questionnaires done within 6 weeks of the 60-day study period, n/N (%) | 64/69 (93) |
|
Completed health care resource use follow-up questionnaires, n/N (%) | 69/76 (91) |
|
Health care resource use questionnaires by phone, n/N (%) | 65/69 (94) |
|
Days after discharge to complete health care resource use questionnaire, mean (SD) | 69 (14) |
|
Completed health care resource use questionnaires done within 6 weeks of the 60-day study period, n/N (%) | 67/69 (97) |
|
Participants who completed all sets of follow-up questionnaires, n/N (%) | 67/76 (88) |
|
Participants who completed no follow-up questionnaires, n/N (%) | 5/76 (7) |
|
Questions completed on received questionnaires, n/N (%) | 4613/4624 (99.8) |
aPackaged follow-up questionnaires included Health Education Impact Questionnaire, Cardiac Self-Efficacy Scale, Morisky Medication Adherence Scale, EQ-5D-5L, and EQ-5D-5L Visual Analog Scale.
Our pilot study assessed the impact, feasibility, and acceptability of a 60-day SMS text messaging program in supporting patients with ACS following hospital discharge. In exploratory adjusted analyses, we did not find statistically significant differences on follow-up scores (controlling for baseline scores where applicable) between the Txt2Prevent group and the usual care group in their self-management domains, health-related quality of life, medication adherence, health care resource use, and self-efficacy in adjusted models, except for the “Total plus” domain, which was impacted by an influential outlier. The study protocol was generally feasible, as seen by high adherence to the study protocol targets for randomization time frames and questionnaire completion rates, although recruitment took much longer than estimated. In terms of acceptability, participants reported they generally found the program acceptable and believed it helped them manage their condition.
In our pilot study, we failed to demonstrate the effect of SMS text messaging on our questionnaire outcomes, including the heiQ, CSE, and medication adherence. Previously, 2 interventions using apps reported improvements in heiQ domains over the short term [
Differences between our findings and others may be due to our intervention’s design. Guided by an advisory committee that included clinicians (a cardiac nurse, a family physician, a community pharmacist, and 2 cardiologists), researchers, and 2 patient partners with lived experiences of CVD, the SMS text messages were education based and included prompts that aligned with hospital messaging and current guidelines [
Regarding the feasibility of the study protocol, we required 17 months to recruit 76 participants instead of the anticipated 6 months. Six months was estimated because there were approximately 750 ACS discharges in the previous year, and a feasibility survey showed 50% (14/28) of patients owned a mobile phone. We assumed 40.0% (300/750) of patients would be eligible and of those 50.0% (150/300) would agree to participate. However, we missed approaching many patients due to restrictions imposed by our ethics board. The research assistant had to obtain bed numbers of patients with ACS from the clinical nurse leader. They then asked the bedside nurse to confirm with the patient if they could explain the study. This required forming strong relationships with clinical staff. Evening recruitment visits also helped as patients were often discharged shortly after returning to the ward from the catheterization laboratory. Ultimately, 43.0% (172/400) of approached patients were eligible and 44.2% (76/172) of eligible patients agreed to participate. More patients declined to participate in our study compared with the 10%-30% refusal rates reported by other CVD SMS text messaging studies that recruited from hospitals or outpatient clinics [
Our study has several limitations to consider. As this was a pilot study, we did not determine our sample size based on power calculations and were likely underpowered to detect clinically important differences. We chose the heiQ as it covers potential proximal and intermediate outcomes of self-management programs [
In our exploratory analyses, we did not demonstrate any positive effects of the SMS text messaging intervention in terms of self-management, medication adherence, health-related quality of life, cardiac self-efficacy, or health care resource use. The Txt2Prevent program had an intentionally simple design and was acceptable to participants, but design changes may be needed before proceeding to a larger study. The study protocol was feasible to implement, although improvements to the recruitment process are likely required. Future work should investigate the effect of tailoring, multifactor versus single-factor interventions, 2-way versus 1-way SMS text messaging, and the effectiveness of behavior change techniques.
Txt2Prevent intervention text messages.
Additional analyses - unadjusted Health Education Impact Questionnaire (heiQ), EQ-5D-5L, EQ-5D-5L Visual Analog Scale (EQ VAS), Cardiac Self-Efficacy (CSE), and medication adherence results at 60-days (controlling for baseline scores).
Additional analyses - 60-day follow-up medication prescriptions, by group.
Additional analyses - physician visits and cardiac rehabilitation enrolment within 60-days, by group.
CONSORT E-HEALTH checklist (v1.6.1).
acute coronary syndrome
analysis of covariance
Cardiac Self-Efficacy scale
cardiovascular disease
EQ-5D-5L Visual Analog Scale
Morisky Medication Adherence Scale
The study received funding from the Canadian Institutes of Health Research (CIHR) through a Catalyst Grant for eHealth Innovations (application number 316822). ER was supported to do this work by a Canada Graduate Scholarships–Master’s Program from CIHR. BS is supported by a Michael Smith Foundation for Health Research (MSFHR) Scholar Award. MM is supported by an MSFHR Scholar Award and a CIHR Embedded Clinician Researcher Salary Award. HV is supported by funding from CIHR and the Ontario Ministry of Health and Long-Term Care’s Health System Research Fund. SL holds the Pfizer/Heart and Stroke Foundation Chair in Cardiovascular Research Prevention at St. Paul’s Hospital, Vancouver, Canada. We acknowledge Mr Daniel Sheinin who was involved in the software development, Ms Nisa Onsel and Ms Joanna Mendell for randomizing study participants, Dr Terry Lee for his statistical advice, the EuroQol Group for their support with the online questionnaire (EQ-5D-5L), Ms Anosha Afaq for her assistance with data entry, and members of the clinical advisory committee, including Ms Alyson Hagan-Johnson (patient partner) and Mr Leon Jung (community pharmacist). We also thank the hospital staff who assisted with recruitment as well as our study participants.
Use of the MMAS is protected by US copyright laws. Permission for use is required. A license agreement is available from Donald E. Morisky, ScD, ScM, MSPH, Professor, Department of Community Health Sciences, UCLA School of Public Health, 650 Charles E. Young Drive South, Los Angeles, CA 90095-1772, dmorisky@ucla.edu or dmorisky@gmail.com.
None declared.