Mobile phone text messaging for improving secondary prevention in cardiovascular diseases: A systematic review

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Heart & Lung j o u r n a l h o m e p a g e : w w w. h e a r t a n d l u n g . c o m

Mobile phone text messaging for improving secondary prevention in cardiovascular diseases: A systematic review Eda Unal a,*, Konstantinos Giakoumidakis b, Ehsan Khan a, Evridiki Patelarou c a Department

of Adult Nursing, Florence Nightingale Faculty of Nursing & Midwifery, King’s College London, James Clerk Maxwell Building, 57 Waterloo Road, London SE1 8WA, United Kingdom Surgery Intensive Care Unit, “Evangelismos” General Hospital of Athens, 45-47 Ipsilantou street, 10676, Athens, Greece c Department of Child and Family Health, Florence Nightingale Faculty of Nursing & Midwifery, King’s College London, James Clerk, Maxwell Building, 57 Waterloo Road, London SE1 8WA, United Kingdom b Cardiac

A R T I C L E

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Article history: Received 10 October 2017 Accepted 12 May 2018 Available online Keywords: Cardiovascular disease Secondary prevention Mobile phone text messaging Systematic review

A B S T R A C T

Objective: The aim of this study was to identify, retrieve, critically appraise and synthesize the existing mobile phone text messaging interventions that have been done for secondary prevention of cardiovascular disease (CVD). Methods: A systematic review was conducted. The searching was conducted by using the MEDLINE, EMBASE, PsychINFO, CINAHL, PubMed and ScienceDirect databases. Nine randomized controlled trials (RCTs) were eligible and included. Results: The preventive factors measured among studies varied. While the majority of studies examined medication adherence as a main outcome (4), the other 3 studies focused of CVD risk factors combining blood pressure (BP), smoking, body mass index (BMI), physical activity and dietary habits, only 2 studies examined both medication adherence and risk factor modification of CVD. Conclusion: Even though mobile phone text messaging may be beneficial for the secondary prevention of CVD, reliable conclusions on the effects of text messaging cannot be drawn. © 2018 Elsevier Inc. All rights reserved.

Introduction Cardiovascular disease (CVD) is the main cause of mortality and morbidity worldwide, and a significantly larger number of people die from CVD per year than from any other cause.1 Approximately 17 million people worldwide die each year from CVD and according to the American Heart Association2 this figure is expected to increase to more than 23 million by 2030. This increase in CVD has been related to successes in acute medical care, resulting in people living longer,3 together with genetic and environmental risk factors. 4 An important proportion of the burden of CVD is preventable,5 therefore, effective secondary prevention manoeuvres can contribute to a reduction in coronary mortality and morbidity.6 These changes include changes to lifestyle; for instance, smoking cessation, weight reduction and prophylactic drug therapy such as angiotensin converting enzyme (ACE) inhibitors,

Conflict of interest: The authors declare that there is no conflict of interest. Funding: This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. * Corresponding author. E-mail address: [email protected] (E. Unal). 0147-9563/$ – see front matter © 2018 Elsevier Inc. All rights reserved. https://doi.org/10.1016/j.hrtlng.2018.05.009

anti-platelet agents.7 Technology plays an important role in the prevention of CVD. Particularly, mobile health technologies have the potential to reduce the cost of healthcare and improve health research and outcomes (Kumar et al., 2013). According to International Telecommunications Union (ITU, 2016) there are more than 7 billion mobile cellular subscriptions in the world and it was found that half of the smartphone owners use their mobile phone to obtain health information (Fox and Duggan, 2012). Mobile phone text messaging is a significant means of communication throughout the world,8 and in more recent times, the use of text messaging or short message service for disease management and prevention has increased.9 Communication between healthcare providers and patients may play a major role in supporting preventive healthcare including disease monitoring and education. 10 For instance, text message reminders for self-monitoring; and patients may report the results of self-monitoring.11 Relevant interventions provide health education to the patients, offer a way of peer to peer networking, supporting self-monitoring of disease and supporting adherence to medication or treatment through text messaging.8 Text messaging may also improve healthcare in other ways 11 ; It is fast, inexpensive and convenient. Transmitted messages can be stored .12 Therefore, in order to promote prevention and management of

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CVD, the use of mobile phone text messaging might provide an effective and innovative approach. A previous systematic review on mobile phone interventions examined prevention of cardiovascular diseases13; it included all mobile phone interventions together, but did not separately consider the use of text messages. There is no study that concentrates singularly on assessing effectiveness of mobile phone text messaging interventions, independent of other technologies and interventions such as email, telephone or video message. Although there are benefits of one form of communication modality over another depending on the aspect of communication being examined, there is some evidence that suggests that rapid viewing and response rates are higher with text messages when compared to email.14 Older people are more likely to possess and use text-enabled mobile phones compared to other internet-based technologies.15 Therefore for the population under examination a good proportion of them may not access technologies, such as video messaging and email. Given these discrepancies the results of the systematic review by Park et al. may not be a true representation of the utility of using text messages alone in secondary prevention of CVD. Therefore, the aim of this review was to identify, retrieve, critically appraise and synthesize the existing only mobile phone text messaging interventions other than multiple interventions that have been undertaken for secondary prevention of CVD. Methods The systematic review followed The Cochrane Handbook for Systematic Reviews of Interventions.16 Titles, abstracts and full texts were screened and reviewed by the first (EU) and second authors (EP), after selection criteria were applied in the search. Identifying and defining the right, clear question is the first step and one of the most significant aspects of undertaking a systematic review (Aveyard, 2014). The purpose of research question is to guide the systematic review, hence, it must be well-defined, answerable and searchable (Ten Ham-Baloyi and Jordan, 2016). PICO format which is the significant components to facilitate the construction of answerable clinical questions (Sacket et al., 2005; Bragge, 2010). It includes following variables: population of interest (P), intervention (I), comparison (C) and the outcomes of interest (O). Therefore, Once the key elements of the question were specified, they were structured and divided into categories (PICO format) in order to develop an answerable clinical research question.16 The population was identified as (patients with cardiovascular disease), the intervention (healthcare related mobile phone text messaging), the comparison (usual care), and the outcome was to promote selfmanagement of existing CVD and risk factor modification in patients with CVD (secondary prevention of CVD) (Table 1). Following formulation using PICO the question produced is “does healthcare- related mobile phone text messaging improve secondary prevention in cardiovascular diseases?”. Search strategy In order to identify all clinical trials about the efficacy of mobile phone text messaging for secondary prevention of cardiovascular Table 1 Breakdown of the review question into the PICO format (P) Population

(I) Intervention

(C) Comparison

(O) Outcome

Patients with cardiovascular diseases

Health-care related mobile phone text messaging

Usual care

Cardiovascular disease secondary prevention outcomes

Table 2 Facet analysis and search strategy (a). Inclusion and exclusion criteria for selecting research papers (b) a Population

Intervention

AND Text messaging (MeSH term) Cardiovascular Diseases (MeSH term) OR OR Short messaga Coronary Artery Disease (MeSH term) OR OR Congenital Heart Defects (MeSH term) Text messaga OR OR Hypertension (MeSH term) Short message service OR OR Heart Failure (MeSH term) Mobile phone messaging OR OR Heart Valve Diseases (MeSH term) Mobile phone text messaging OR Peripheral Arterial Disease (MeSH term) OR Stroke (MeSH term) b Inclusion

Exclusion

Studies in English and Turkish language Randomized controlled trials Studies published during the last 10 years (2006–2016). Male and female adult (≥18 years old) patients Studies that involved control group Studies that have both one way and two ways text messages Studies with mobile phone text messaging interventions

Studies assessing multiple modalities Studies that involved teenagers and child populations

a

truncation.

diseases, internet-based literature searching was performed. The searching was conducted by using the following six databases: MEDLINE via OVID, EMBASE via OVID, PsychINFO, CINAHL, PUBMED and ScienceDirect in order to identify comprehensive, published recent papers to provide the best evidence. A facet analysis was applied to provide a more focused search and to increase sensitivity (Table 2). Key terms associated with the research question were combined utilizing Boolean operator commands (OR, AND). Boolean operators were utilized to narrow and broaden the search field to obtain the best outcome. The Boolean operator ‘OR’ brings the all identified terms together in order to increase the sensitivity of the findings. In contrary, the Boolean operator ‘AND’ was used to increase specificity of the findings by narrowing down the search and identifying articles that addressed elements of the PICO. Truncation (*) was applied where appropriate to enhance the search. Eligibility criteria Male and female adult patients (≥18 years old) with any types of cardiovascular diseases were included in this review. Cardiovascular diseases could include acute coronary syndrome, high blood pressure, heart failure, stroke, heart valve and peripheral arterial diseases. Studies which were conducted among teenagers and children with for example congenital heart diseases were excluded. Studies had to assess the effectiveness of mobile phone text messaging for secondary prevention of CVD. Studies utilizing both one way and two ways text messages were also included. Text messages that delivered a reminder to take medication or information regarding diet, exercise and smoking were considered a valid text message intervention. Studies assessing multiple modalities (website, email, apps, video, web portal, phone call), other than mobile phone text messaging were excluded. This is because studies assess

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comprehensive intervention package with text messaging as a component, and therefore it will not be possible to separate the effects of text messaging alone.16 Moreover, it is possible that one type of intervention affects the other interventions. See Table 2 for inclusion and exclusion criteria to select eligible studies. Data extraction and quality assessment The CONSORT statement checklist (2010) was used to assess the quality of reporting in the studies.17 Quality assessment of the individual studies was performed by two reviewers independently (EU and EP). They were assessed according to their eligibility, appropriateness, rigour, honesty, methodology chapters’ transparency, results, discussion and outcomes.18 Types of studies The included studies for this review were all Randomised Controlled Trials (RCTs) that evaluated the effectiveness of healthcarerelated mobile phone text messaging in secondary prevention of cardiovascular diseases in patients with CVD changes in multiple risk factors and quality of life. RTCs are regarded as the ‘gold standard’ for evaluating selected effective treatment19; therefore, when resources, feasibility and ethical considerations are taken into consideration, a RCT study seems to be the best method in order to address the question in this review. Results Search findings A total of 742 articles were found through searching from the following databases: Medline (n = 88), Ovid Embase (n = 234), PsychINFO (n = 16), Pubmed (n = 122), CINAHL (n = 33) and ScienceDirect (n = 249). A total of 206 papers were identified to be duplicates and they were removed. Then the rest of the articles (n = 536) were initially screened, of which 516 were excluded by reviewing the title (n = 482) and after reading the abstract (n = 34) using the inclusion/exclusion criteria. A total of 20 full-text versions of the remaining studies were read and assessed for meeting the inclusion criteria. Eleven articles were excluded as they did not meet the inclusion criteria. In order to clarify the process of selection studies, a summary of the study selection is shown in Figure 1 by using the PRISMA flowchart.20 Main characteristic of studies Nine RCTs were included in this review. Studies were published between 2012 and 2016, and their published language was English. Even though the Turkish language was also inclusion criteria for the systematic review, no Turkish trial was found during database searching. All nine studies included comprising 3637 patients with any type of CVD. All the trials in the present study were conducted in different countries, including Australia (Sydney),21 France,22 Iran (Isfahan),23 Malaysia (Kuala Lumpur),24 Pakistan (Karachi),25 Russia (Saratov),26 South Africa (Cape Town),27 the UK (London),28 the USA (California)29; therefore, it was not likely that the same patients were included in different publications. Study sample sizes ranged from 62 to 1372 patients: 6 studies23–26,28,29 had < 500 patients, 2 studies21,22 had 500 to 1000 patients, 1 study27 had > 1000 patients. The review includes studies targeting 4 cardiovascular conditions: Hypertension (HTN) (4),23,26–28 coronary heart disease (CHD) (3),21,22,29 stroke (1)25 and acute coronary syndrome (1).24 While the majority of studies examined medication adherence as a main

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outcome (4),22,24,28,29 the other 3 studies21,26,27 focused of CVD risk factors combining blood pressure (BP), smoking, body mass index (BMI), physical activity and dietary habits, only 2 studies23,25 examined both medication adherence and risk factor modification of CVD. Duration of the studies differed which ranged from 1 month to 1 year: 2 studies22,29 had follow-up of 1 months, 2 studies24,25 had follow-up for 2 months, 3 studies21,23,28 had follow-up of 6 months, 2 studies26,27 had follow-up for 1 year. Participants in studies were recruited based on a CVD and regular access to a mobile phone and they were recruited from different settings: 3 studies22,24,29 recruited patients from hospitals, whereas 3 of them25,27,28 recruited from clinics. 1 of them26 recruited from the Research Institute of Cardiology. Lastly, the other 2 recruited21,23 from both clinics and hospitals. The mean age of participants was ranged from 4926 to 6424 years in the intervention group and between 5126 and 6424 years in the control group. The definition of usual care differed among studies, however, 4 studies explained usual care as a follow-up visits.21,24,25,27 Consultation with a doctor was defined as a usual care in 1 study,23 while one other study24 described it both for cardiac rehabilitation and follow-up visits. In 2 studies22,23 usual care was not defined by the study authors. The main characteristics of the included studies are shown in Table 3. Mobile phone text messaging characteristics The studies’ mobile phone text messaging characteristics are presented in Table 4. While 3 trials25,26,28 used bi-directional text messaging by allowing communication between the study team and participants, the other 6 trials21–24,27,29 restricted mobile phone text messaging transmission to one-way (only study team sending the text messages). Three studies that requested two-way messaging did neither offer financial contribution nor reimbursement.25,26,28 The total number of text messages and the dose of SMS also differed in the studies. Bobrow et al. (2016) sent the highest number of SMS in total (90,060), but they did not state how often they were sent.27 Frequency of SMS varied daily and weekly among studies which is shown in Table 4. The mobile phone text messaging was used as an intervention for different purposes in the studies. SMS types were sorted into 3 categories: SMS that a reminder to medication (3)22,24,28 sent daily in 1 study,22 daily for two weeks, then alternate day for two weeks, then weekly for 22 weeks in 1 study28 and it was depended on patients in 1 study24; SMS to provide education about lifestyle modification for example about dietary habit, smoking, physical activity (1),21 sent 4 SMS every week in this study21; or both of them (4)23,25–27,29 to direct patients. Of 2 studies23,27 did not state the frequency of SMS. In addition, five trials used webbased programs to send e-messages,21,24,26–28 four trials did not explain how the messages were sent to the patient.22,23,25,29 Analysis of outcomes Outcomes measured among studies varied including medication adherence, blood pressure level (systolic and/or diastolic), smoking, physical activity and body mass index and dietary habits of patients. Medication adherence Six trials reported medication adherence, which is an important public health issue. Four of the six trials reported the effects of mobile phone text messaging22,24,25,28; however, two of trials did not report statistically significant improvement on medication adherence in patients receiving reminder messages, with a p-value of 0.223 and 0.37.29Studies measured the level of medication adherence in different ways, including personal inquiry at clinic visits,28 electronic medical record,28,29 oral and paper questionnaire22,23 and

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Fig. 1. Selection of studies for inclusion in this systematic review.

the Morisky Medication Adherence Scale (MMAS),24,25,29 is a wellvalidated self-report questionnaire to assess behaviour about taking medication, and adherence with well predictive validity.30 Moreover, only two studies reported mean medication adherence scores of MMAS; in Kamal et al.’s (2015) study, there was a much larger improvement in the intervention group (7.4) than control group (6.7) (p-value < 0.01). However, the score was lower than 7 in Park et al.’s (2014) study with a p-value of 0.37 (intervention group: 6.43, control group: 6.96). It should be noted that mHealth interventions are in the early stages in the research, therefore, there is no widely accepted standard effect size for medication adherence trials. Modifiable risk factors Three of the studies reported improved BP outcomes in their intervention group compared with the control group21,25,26; however, one trial found small reduction with a −2.2 mean difference and narrow 95% CI (−4.4 to −0.04) in systolic blood pressure in pa-

tients receiving mobile phone text messaging.27 Nonetheless, the use of mobile phone text messaging demonstrated no significant difference in patients’ BP in two studies.23,28 Behavior that was targeted for BP was medication adherence, physical activity, stopping smoking, dietary approach (eating a diet rich in vegetables and reduction of dietary sodium to below 1500 mg/day)23 Although BP was measured by looking at the mean difference before trial and after trial in four studies,21,23,25,27 one of them that used achievement goals to ascertain if candidates achieved identified BP targets.26 Kiselev et al. (2012) reported a statistically significant p- value (p: 0.005) that 77% of intervention group had achieved goal BP level which was also clinically significant (95% CI: 3.2 to 9.9). In addition, while systolic BP was lower in Bobrow et al.’s (2016) and Chow et al.’s (2015) study (MD: −2.2 and −8 respectively), Kamal et al. (2015) found significant difference in diastolic blood pressure. Two studies21,28 reported low-density lipoprotein cholesterol (LDLC). One of them21 had a modest improvement with a p-value of 0.04.

Table 3 Main characteristics of the studies included in the systematic review (n = 9) Author, year & setting

Intervention

Control

Outcomes

Hypertensive studies Bobrow et al., 2016 South Africa

1 year

1372 hypertensive patients Mean age: 54.3

(n:457) Usual care which was defined as a routine clinic visits

Small reduction in systolic BP level MD: −1.6 (−3.7 to 0.62)

Golshahi et al.,2015 Iran

6 months

180 hypertensive patients Mean age: Intervention:56.76 Comparison:57.51

(n:45) Usual care, which was not defined by the study authors

No significant changes in all self-care behaviours and BP level as well as medication adherence.

Kiselev et al.,2012 Russia

1 year

199 hypertensive patients Mean age: Intervention:49 Comparison:51

(n:102) Usual care which was defined as an only consultation with a doctor in the office.

There were no significant changes in BMI or smoking, however, BP goals were achieved in 77% of intervention group (p < 0.05).

Wald et al.,2014 London

6 months

303 hypertensive patients Mean age: Intervention:60 Comparison:61

(n:458) Personalized SMS focusing on information about social support, goals, planning and natural consequences of hypertension (n:45) Educational SMS about medication adherence and self-management behaviours including diet, smoking, physical activity and BP (n:97) SMS reminding to perform doctor’s recommendations about home BP monitoring, treatment, correction of BMI and smoking Collection of data on BP, body mass and number of smoked cigarettes by patient Scheduling of patients for office visits (n:151) SMS reminders on medication adherence

(n:152) No SMS to remind medication

Significant difference on medication adherence p < 0.001; no significant changes in BP and cholesterol

Coronary heart disease studies Park et al.,2014 USA

1 month

(n:30) SMS reminders on medication adherence

(n:30) No SMS to remind medication

No significant difference in patient reported medication adherence p = 0.37

Quilici et al.,2013 France

1 month

(n:262) SMS reminders on medication adherence

(n:259) Usual care which was not defined by the study authors

Significant difference in medication adherence by platelet aggregation testing p = 0.01

Chow et al.,2015 Australia

6 months

90 CHD patients Mean age: Intervention:58.2 Comparison:61.1 521 CHD patients Mean age: Intervention:64 Comparison:64 710 CHD patients Mean age: Intervention:57.9 Comparison:57.3

(n:352) Semipersonalized SMS about CHD risk factors providing advice, motivational reminders, information to improve diet, to increase physical activity and to encourage smoking cessation

(n:358) Usual care which defined as follow-up visits.

Modest improvement in LDL-C level (p:0.04) MD:−5(−9 to 0) moderate improvement in systolic BP, BMI, physical activity and smoking status

Stroke studies Kamal et al.,2015 Pakistan

2 months

200 stroke patients Mean age: Intervention:56 Comparison:57.6

(n:100) SMS reminders on medication adherence

(n:100) Usual care which was defined as a regular follow-up visits

Significant difference on medication adherence MD: 7.4 (7.2–7.6) (p < 0.01), no significant changes in BP MD: −2.6 (−5.5 to 0.15)

Acute coronary syndrome studies Khonsari et al.,2015 Malaysia

2 months

62 acute coronary syndrome patients Mean age: Intervention:56 Comparison:59

(n:31) SMS reminders on medication adherence

(n:31) Usual care which was defined as a cardiac rehabilitation and follow-up visits

Significant difference on medication adherence p < 0.001

BMI, body mass index; BP, blood pressure; CHD, coronary heart disease; SMS, short message service.

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Table 4 Type and length of mobile phone text messaging Lead author and date

Type of SMS & Transmission

Total number of SMS

Frequency of SMS

Bobrow et al., 2016

Reminder to medication Education on hypertension and its treatment (one-way text messaging) Advice, motivation and information about diet, physical activity and smoking (one-way text messaging) Reminder to medication Education on lifestyle modification (physical activity, vegetable intake, smoking) (one-way text messaging) Reminder to medication Health information (two-ways text messaging) Reminder to medication (one-way text messaging) Reminder to perform doctor’s recommendations about home BP monitoring, treatment, correction of body mass and smoking and reminder to medications (two-ways text messaging) Reminder to medications Education on CVD risk reduction (one way text messaging) Reminder to medication (one way text messaging) Reminder to medication (two-ways text messaging)

90,060

It was not stated in the study

96

4 SMS per week

It was not stated in the study

It was not stated in the study

At least 76 but the exact number was not stated in the study

Reminder to medication = daily Health information = twice a week

It was not stated in the study

depending on patient

At least 104 but the exact number was not stated in the study

SMS request about the number of smoked cigarettes and body mass index = once a week Reminders about drugs = daily or weekly

88

30

Reminder to medications = twice a day Education on CVD risk reduction = three times a week Once a day

At least 37 but the exact number was not stated in the study

Daily for two weeks, then alternate day for two weeks, then weekly for 22 weeks

Chow et al., 2015

Golshahi et al., 2015

Kamal et al., 2015

Khonsari et al., 2015 Kiselev et al., 2012

Park et al., 2014

Quilici et al., 2013 Wald et al., 2014

However, there were no statistically significant differences in LDL cholesterol in Wald et al.’s (2014) study. The other modifiable risk factors were reported in the other three trials21,23,26 including BMI, smoking, physical activity and dietary modification. There were no statistical changes in two studies23,26 on BMI, physical activity, diet and smoking; whereas they were significantly better in intervention group in Chow et al.’s (2015) study (p: < 0.001 for BMI, p: < 0.001 for physical activity and p: < 0.001 for smoking).

Detection bias Two studies were judged as a high risk of bias because they did not blind people who assess the outcome.21,23 Three studies precisely explained their assessment process and their assessors were not aware of the study group assignment, therefore, they were perceived to have a low risk of bias.24,25,27 The other four trials gave insufficient information to permit judgement low or high risk of bias; thus, they were judged to have unclear risk of detection bias.22,26,28,29

Quality ratings Cochrane Collaboration’s tool was used to assess the risk of bias in each individual study.31 Risk of bias for included RCTs in this review is summarized in Figure 2. Selection bias The random sequence generation and allocation concealment of the recruited participants in these RCTs except 322,24,26 were stated precisely. Of which 4 trials,23,25,27,28 used block randomization to randomize patients between experimental and control groups. In 3 studies, the participants were randomly distributed via a webbased randomization program and, therefore, were categorised as presenting low risk of bias.21,27,28 Only 2 studies used a sealed opaque envelope and this was classified as a low risk of bias.25,29 The other 3 studies did not state any information regarding the method used for allocation concealment and those were categorised as presenting an unclear risk of bias owing to lack of specification.22,23,26 Performance bias Three studies did not mention blinding of participants and personnel; therefore, they were classified as presenting unclear risk of bias.22,26,28 Three studies failed to blind their personnel due to the nature of the procedure and for that reason they were classified as showing high risk of performance bias.23,24,29 The other three studies were categorised as low risk of bias in terms of blinding participant and personnel because they mentioned how this process was performed and how they achieved.21,25,27 Trial statisticians, clinic staff, researchers and research assistants were blinded in these trials.

Attrition bias Four trials gave clear and meaningful descriptions whether they performed analysis of missing data properly; therefore, they were perceived to have low risk of bias.21,24,25,29 The other two studies clearly and sufficiently reported their reason for the missing data; therefore, they were perceived to have a low risk of bias.26,28 Furthermore, Golshahi et al. (2015) were judged to have low risk of attrition bias because all participants were followed-up until the end of study. All data were analysed with intention to be treated in Bobrow et al.’s (2016) study; thus, there was no sufficient reason for the missing data. As a result, this study was classified as having an unclear risk of bias. Only one study did not address this outcome.22 Reporting bias For three studies, protocols were available; hence, they were classified as having a low risk of selective reporting bias.21,27,28 The study performed by Khonsari et al. (2015) was judged to have a low risk of bias because it is clear from the published results that they included all expected outcomes. Nevertheless, in five studies that provided information regarding the findings, their data were found as inadequate; thus they were classified as having an unclear risk of bias.22,23,25,26,29 Other potential sources of bias All patients participating in the trial provided written informed consent and it was reported in the studies. Of the seven trials,21,24–29 except one22 obtained ethical approval from the ethics

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Study

Random sequence generation

Allocation concealment

Blinding of participants and personnel

Blinding of outcome assessment

Incomplete outcome data

Selective reporting

Other potential sources of bias

Chow et al. 2015

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Bobrow et al. 2016

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Park et al. 2014

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Wald et al. 2014

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Khonsari et al. 2015

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Kiselev et al. 2012 Kamal et al. 2015 Golshahi et al. 2015

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Quilici et al. 2013

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+= Low risk

-= High risk

?= Unclear risk

Fig. 2. Risk of bias summary: judgements about each risk of bias item for each included study.

committee and it was specified in all studies; therefore, they were judged as a low risk of bias. Quilici et al. (2013) did not report ethic approval of the trial; hence, it was classified as a high risk of bias. Golshahi et al. (2015) perceived to have an unclear risk of bias because of inadequate information to assess if an important risk of bias exists. Discussion This systematic review sought to evaluate the evidence for the effectiveness of mobile phone text messaging intervention that address multiple existing CVD self-management behaviours in the secondary prevention of cardiovascular disease. To the best of our knowledge, this review is the most recent systematic review focusing specifically on mobile phone text messaging as an intervention other than multiple interventions to improve secondary prevention of CVD. We identified nine RCTs that measured the impact of mobile phone text messaging interventions on overall CVD outcomes and/or multiple CVD conditions. Our review of nine mobile phone text messaging studies found that majority of the trials were effective in outcomes of CVD and in improving behaviour modification. Moreover, the result of this systematic review confirms that even though the population of the participants in trials consisted of older CVD patients, the majority of studies had positive outcomes. This review represents diverse cardiovascular conditions where four of nine studies addressed hypertension as the primary condition, while of three trials focussed on CHD, the remaining two addressed stroke and acute coronary syndrome respectively. The most commonly measured outcome was medication adherence and the second one was BP, as well as, other modifiable risk factors including diet, smoking, physical activity were measured by three studies. 21,23,26 The majority of studies found improvement on

medication adherence in patients with CVD except for two studies.23,29 On the other hand, this review revealed that half of the trials examining BP did not find reduction in BP and no improvement on the other self-care behaviours. Duration of the studies and frequency of SMS intervention differed widely, causing challenge to compare the findings of the trials and limited our ability to make inferences the optimal length and frequency of SMS utilization effect. A comparison of Quilici et al.22 (2013), Kamal et al.25 (2015), and Wald et al.28 (2014) showed noticeable differences in length of the studies (1, 2 and 6 months, respectively), implying that not only personalized medication reminder messages but also the content and the frequency of messages might have had large impacts on adherence to medication than study duration alone. Although the duration of the Khonsari et al.’s (2015) study and Park et al.’s (2014) study was less than 6 months, Khonsari et al. (2015) demonstrateda significant behavioural outcome result. However, Park et al. (2014) did not contribute any significant selfcare outcome. This may be because of the simplicity and practical content reported in in Khonsari et al.’s (2015) study with the frequency of messages sent depended on patients in the intervention. Conversely, Park et al. (2014) sent SMS twice a day, the content was not clearly identified in the study. Therefore, it is noteworthy that the number of SMS on a daily basis might be overwhelming for the patients; however, according to the available evidence, it is challenging to express the exact dosage of text messages. A possible conclusion that can be drawn is that there should be a balance regarding how often health-related text messages should be sent to CVD patients and this frequency may depend on patients’ circumstances. The findings of this study have similar results of a prior review showing that overall potential improvement on various CVD condition outcomes.32–35 It is found from Horvath et al.32’s (2012)

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systematic review that mobile phone text messaging is an effective way to promote adherence in patients with HIV infection. Similarly, Finitsis et al.33 (2014) reported that mobile phone text messaging can improve antiretroviral therapy adherence. Although less frequent than daily messages were more effective in Finitsis et al.33’s (2014) study, no evidence was found related to frequency in this systematic review. Furthermore, a systematic review published in 2013 that included four studies on the use of mobile phone text messaging to promote medication adherence in antituberculosis patients found that mobile phone text messaging interventions have a potential to improve patients’ tuberculosis treatment34 which is consistent with the findings of this review. Vargas et al.35 (2016) found mobile phone text messaging could be a practical and influential instrument for management of hypertension. However, the result contrasts with the result of this review. One possible explanation for this might be that rather than focussing on mobile phone text messaging alone, their included studies had text plus other components including telephone coaching36 and web-based diary.37 It is likely that, multiple interventions could have influenced each other leading to a composite change on outcomes. In addition, another limitation to interpret Vargas et al.35’s (2016) review is that although there were three existing RCT which were eligible for their inclusion criteria,21,23,27 they did not add these three trials to their systematic review. leading to the possibility that these three studies may have altered their result. Strengths and limitations This was the first systematic review that has attained and assessed evidence for mobile phone text messaging in secondary prevention of cardiovascular diseases. The main strength of the present review was that it only focuses on mobile phone text messaging interventions. One weakness of this review was the decision to exclude pilot studies since these reduced the amount of available evidence for critical appraisal of the review. However, it should be considered that this decision was made in keeping with the hierarchy of evidence to provide that the highest quality of evidence was used, and RCTs being noted as the gold standard for research. It is believed by researchers that all the studies concerning the use of mobile phone text messaging for secondary prevention of CVD have been identified. Even though not all studies clearly explained all related details, one of the strengths of this systematic review were that all the trials were randomised and all studies conducted in different countries have both low and high resource settings; hence, it is reasonable to generalise these findings globally. Implication for practice Mobile phone text messaging might be beneficial to remind patient’s medication or it may influence lifestyle behaviours such as diet, physical activity and smoking; however, little information is known regarding health effects, adverse effects and harms, satisfaction of the users with the intervention and the users’ perceptions of its safety. For example, it is important to bear in mind that there is increased risk of car accidents as a result of text messaging while driving.10 Therefore, current evidence still maintains inadequate to provide precise information in order to inform policy decisions. Moreover, it is noteworthy that when text messaging is implemented in low resource settings, potential barriers should be taken into consideration. these may include poor literacy, vision problems, language barriers, privacy and disclosure issues, the inability of people to charge their battery of mobile phones owing to lack of electricity and the high rate of mobile phone theft.34 For instance, misinterpretation and misunderstanding of the messages

for people who have difficulty in reading is inevitable due to poor literacy and vision problems.10 In addition, messages do not cover verbal and non-verbal communication; therefore, it might also cause misinterpretation of the content of the message.8 Implication for research All studies in this review except two21,27 used small sample sizes. This means that future research would benefit from using larger sample sizes and there is a need for more high-quality RCTs of mobile phone text messaging on lifestyle modification of CVD. The included RCTs did not look at cost-effectiveness of mobile phone text messaging; therefore, in future research, cost efficiency should be considered. Patients with CVDs in the included studies were recruited from different countries (Russia, France, Malaysia, Australia, Pakistan, Iran, South Africa, the USA and the UK). This means that the ethnicity of participants varied among studies. Five of the studies reported that they had participants from different ethnicities, such as Malay, Arab, Indian, Chinese21,23,24,27,29; nevertheless, four trials did not provide any characteristic features related to ethnicity22,25,26,28 it is well-known that London is a cosmopolite city which has a great number of people from different nations; therefore, Wald et al.28 (2014) should have been reported the ethnicity of patients. It means that the inter-relationship among ethnicities needs to be studied further since different ethnicities might have different preferences for a text messaging service. Conclusion Even though the evidence presented in this review shows that mobile phone text messaging may be beneficial for the secondary prevention of CVD, reliable conclusions on the effects of text messaging cannot be drawn. Due to the variability in the quality of the included studies and the limited evidence as to the effectiveness of text messaging for CVD patients and further research is needed before widespread implementation of this intervention. Future investigations should try to examine health outcomes, costs, economic benefits, patients’ and healthcare providers’ evaluation of the intervention, potential harms and adverse effects of mobile phone text messaging. Moreover, in future research the frequency and the content of text messaging should be considered. References 1. World Health Organisation. ‘Cardiovascular Diseases (CVDs); 2017. http:// www.who.int/mediacentre/factsheets/fs317/en/. Accessed December 23, 2017. 2. American Heart Association. Heart disease and stroke statistics–at-a-glance; 2017. https://healthmetrics.heart.org/wp-content/uploads/2017/06/Heart -Disease-and-Stroke-Statistics-2017-ucm_491265.pdf; Accessed December 23, 2017. 3. Neubeck L, Redfern J, Fernandez R, Briffa T, Bauman A, Freedman SB. Telehealth interventions for the secondary prevention of coronary heart disease: a systematic review. Eur J Cardiovasc Prev Rehabil. 2009;16:281–289. 4. Woods SL, Froelicher ESS, Motzer SA, Bridges EJ. Cardiac Nursing. Philadelphia, PA: Lippincott Williams & Wilkins; 2010:550–585. 5. Mendis S, Puska P, Norrving B. Global Atlas on Cardiovascular Disease Prevention and Control. World Health Organization; 2011. 6. Clark AM, Dalal HM, Dafoe W, Stone JA, Lewin RJ. Effectiveness of secondary prevention programs in CHD. Lancet. 2009;373:1671. 7. Clark AM, Hartling L, Vandermeer B, McAlister FA. Meta-analysis: secondary prevention programs for patients with coronary artery disease. Ann Intern Med. 2005;143:659–672. 8. Vodopivec-Jamsek V, de Jongh T, Gurol-Urganci I, Atun R, Car J. Mobile phone messaging for preventive health care. Cochrane Database Syst Rev. 2012;(12):CD007457. 9. Albright K, Krantz MJ, Jarquín PB, DeAlleaume L, Coronel- Mockler S, Estacio RO. Health promotion text messaging preferences and acceptability among the medically underserved. Health Promot Pract. 2015;16:523–532.

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