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A SYSTEMATIC REVIEW AND META ANALYSIS OF RANDOMISED  

CONTROLLED TRIALS EVALUATING THE EFFECTIVENESS OF  

MOBILE PHONE TEXT MESSAGING AS A SUPPORTIVE  

INTERVENTION IN THE MAINTENANCE OF GLUCOSE CONTROL  
  

  

Emmanuel O. Chukwu1 and Olive C. Ibeto2  
1Medical Unit, Diana Princess of Wales Hospital, Grimsby, United Kingdom 2Department of Public Health, 

University of Chester, United Kingdom  

 

Abstract  

Background: Poorly managed Diabetes results to unbearable complications, at high expense to the health 

system. Mobile phone text messaging can be an ideal platform in rendering self-management care to diabetic 

patients, which in essence improves the blood glucose control. The main aim of this study is to evaluate 

systematically, the effectiveness of Mobile phone text messaging as a supportive intervention in the maintenance 

of glucose control.  

Methods: Various databases such as Cochrane Library, PubMed, Medline, Embase were searched following a 

timeline between the 1st of January 2004 to 1st of August 2019.   Reference list from significant studies as well 

as included studies were reviewed for additional studies. Randomised controlled trials (RCT) evaluating the 

effect of text messaging on haemoglobin concentration were well utilised in this review.  

Results: Seven studies were included in the investigation for this review, having met the inclusion criteria.  

Reports from five of the studies stated that the intervention group had significant decrease in haemoglobin 

concentration, when compared to the control arm. It was observed from the meta-analysis that the impact of 

Mobile Phone Text Messaging (MPTM) on glucose control was effective (MD = -0.53, 95% CI= -0.75, 0.30, P 

< 0.00001).  

Conclusion: Mobile phone text messaging can render supportive care towards improving health outcomes 

amongst diabetic patients. This can be achieved by enhancing the individual’s knowledge and self-efficacy, 

which would significantly assist in self-management.  

 

Keywords: Systematic, Review, Meta-Analysis, Randomised, Trial, Controlled, Effectiveness, Mobile Phone, 

Supportive, Intervention, Maintenance, Glucose, Control  

  

Introduction  

Diabetes Mellitus (DM) is a known long-lasting disease that badly affect lots of individuals globally, which 

result to significant mortality, morbidity and excessive utilization of resources in health care facilities (WHO-

World Health Organization, 2020). This disease condition has continuously placed unmatched pressure on the 

health care schemes globally (Lin et al, 2020; Kitsiou, Pare, Jaana, & Gerber, 2017). The incessant and 

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predictable increase in the incidence of DM in addition to the expenses resulting from the lasting effects of this 

disease condition, have drawn the mind-sets of the health care providers and the policy makers on focussing on 

how best to enhance diabetes care and patient’s outcomes, utilising self- management interventions (Powers et 

al., 2017).    

DM is a known chronic ailment that occurs as a result of the inability of the pancreas to produce adequate insulin 

or when the body finds it difficult utilising effectively, the insulin produced (American Diabetes Association-

ADA, 2010). The chronic increase in the blood sugar level which results from uncontrolled diabetes leads to 

lasting damage effect and the inability of some vital organs in the body to function. This effect includes possible 

loss of vision (retinopathy), renal failure (neuropathy), and neuron disorder (neuropathy) (Liu et al, 2020; Lotfy, 

Adeghate, Kalasz, Singh, & Adeghate, 2017).  This disease condition has been among the most common long-

lasting diseases experienced all over the world and has gradually remained on the increase in terms of prevalence 

and significance (Khan et al, 2020).  

DM can be viewed as a group of metabolic diseases traditionally associated with high levels of glucose in the 

blood that causes problems in insulin production and insulin use, or both (ADA, 2010). Recently, WHO 

announced the gradual rise in the prevalence of DM over the past years, around the world (WHO, 2019). The 

International Diabetes Federation (IDF) global estimate showed that approximately 415 million adults were 

living with diabetes mellitus in 2015 with a projected increase of about 642 million by the year 2040 (Ogurtsova 

et al., 2017). Developing and under developed countries are the hardest hit by the burden from the disease 

condition, as approximately 80% of DM cases occur in these nations (Zhang et al., 2010).  

It has been stated from researches that 14.2 million adults in Africa between the age range of 20 and 79 years 

are diabetic, and are estimated to rise to 34.2 million by 2040 (Mbanya, Motala, Sobngwi, Assah, & Enoru, 

2010). Notwithstanding, the high prevalence of DM recorded about 193 million individuals representing that up 

to half of the population living with DM are unaware of their condition (Fan, 2017). Continentally, the 

approximated prevalence of DM is in Africa was 3.8%, 10.7% in the North and Middle  

East of Africa, 7.3% in Europe, 11.5% in the Caribbean and Northern America, 9.6% in the Central and Southern 

part of America, 9.1% in the South-eastern part of Asia, and 8.8% in the Western Pacific (Fan, 2017). High 

populated Countries such as the United states, China, and India, have continually being on the increase in terms 

of prevalence of individuals living with DM (WHO, 2016). In the United Kingdom (UK), there is a 6% 

prevalence of DM among individuals between 20 and 79 years (Diabetes UK, 2018). Similarly, the American 

Diabetes Association (ADA), in 2011 estimated that 25.8 million adults and children were being diagnosed with 

DM (Control & Prevention, 2011).   

The two major types of DM include Type 1 and Type 2 DM (WHO, 2019). Type 1 DM which was once 

identified as insulin dependent diabetes or juvenile diabetes occurs as a result of the pancreas producing little 

or no insulin (WHO, 2018). Type 1 DM, according to the WHO is not preventable. Type 2 DM occurs as a 

result of the body’s inability to effectively utilise insulin. It occurs more in adult; however recent studies 

indicated that Type 2 DM is now also increasingly found amongst children and adolescents (WHO, 2018). 

Majority of the diabetic patients globally, fall under the category of Type 2 DM.  Unlike Type 1 DM, Type 2 

DM is highly preventable (WHO, 2019). Other specific types of DM include Gestational DM, which is 

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characterised by increased blood glucose level in pregnancy. The major clinical manifestations of the disease 

condition include Polyuria (excessive urine), Polydipsia (excessive thirst), Polyphagia (excessive hunger) and 

weight loss (ADA, 2011). Identification of hyperglycaemia plays an important factor in the diagnosis of DM.  

The International Expert Committee suggested that the diagnosis of diabetes be made based on the measurement 

of the haemoglobin (HbA1c), which in effect signifies the lasting blood glucose concentration (Gillett, 2009). 

The diagnostic criteria include HbA1c greater than or equal to 6.5% (48mmol/mol), or Fasting plasma glucose 

greater than or equal to 7.0mmol/L (126mg/dl) or 2- hr Plasma glucose greater than or equal to 11.1mmol/L 

(200mg/dl) (Sacks et al., 2011).  

Research Methods  

Research Aims and objectives  

  This study was aimed at extracting a pooled estimate of RCTs comparing the effectiveness of Mobile Phone 

Text Messaging intervention in combination with normal standard care as compared with standard care alone 

for glycaemic control in diabetes management. This study achieved the principle aim by accomplishing the 

following objectives;  

i. Critically reviewed conducted RCTs that focused on mobile phone text messaging as an intervention for 

improving healthcare service delivery. ii. Critically reviewed conducted RCTs that focused on mobile phone 

text messaging as an intervention for improving glycaemic control in diabetes self-management.  iii. Analysed 

the identified and included RCTs using statistical tools such as Standard Deviation, p-values, and confidence 

interval, to evaluate the intervention under study seeking for evidence of significant effectiveness.  

iv. Provided recommendations based on rejected or accepted proposed hypothesis on the best possible 

approaches towards providing an excellent healthcare service.  

Research Question  

This review, just like other studies aims to provide an answer to a theoretical question. In meeting up the aim 

of carrying out a systematic review, the research question to be focussed on, was stated as: Is Mobile Phone 

Text Messaging Effective as A Supportive Intervention in The Maintenance of Glucose Control?  

Research Hypothesis  

This study includes both null and alternative hypothesis.   

The null hypothesis states that there is no effect or improvement in glucose control amongst diabetic patients 

that utilised MPTM in comparison to individuals on standard treatment only. Alternative hypothesis states that 

a significant effect was observed in the glucose control of the patients that used MPTM in comparison to 

individuals who were on standard treatment only.  

Inclusion Criteria  

• The criteria include that all studies utilised must be Randomised controlled trials conducted within a 

time frame of 15 years 01/01/2004 to 01/08/2019. RCTs were used in this study because of its quality in terms 

of assessing and evaluating therapeutic efficacy, hence right for answering the research question (Stern et al., 

2014).   

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• The participants in this research were diagnosed of Diabetes Mellitus. Type 1 or Type 2 DM to be 

specific. Studies utilised in this study assessed the effectiveness of MPTM amongst Type1 or Type 2 DM, and 

the comparator is the use of standard diabetic care only.   

• Studies utilising HbA1c in measuring glucose control, prior and after the intervention were included.   

• Ages of participants in this study were between 8 and 75 years old.  

  

Exclusion Criteria  

They include the following:  

• All trials that were not randomized controlled trials.   

• Trials conducted on other types of DM except Type 1 or Type 2 DM.    

• Trials that compared MPTM with other health conditions apart from Type 1 and 2 DM.   

• Studies that compared MPTM and other information technology interventions were not included.   

• Studies including pregnant women were not included.   

It was vital to exclude such studies as the research design for this review majorly concentrates on comparing 

the use of MPTM and standard care with the use of standard care only. Incomplete and ongoing studies were 

excluded from this review too.   

Studies Included  

The randomized controlled trial studies utilized in this review were conducted in, New Zealand, Egypt, 

Philippines, South Korea, Scotland, Mexico, and Iran, evaluating the effectiveness of MPTM in combination 

with standard care, and standard care alone. Comparative RCTs are regarded as gold standard for accessing the 

effectiveness of public health interventions using systematic review methodology. Seven Randomised Control 

Trials were selected for this review after a systematic search. Studies selected used literate participants that 

owned mobile phones, and are able to speak, read, and understand text messages in English Language. These 

studies used standard care only as a comparator, Studies with clinically certified diabetic patients whose HbA1C 

levels are greater than 7%. were used. Studies that were accessed to be of low quality were also excluded from 

this study.  

PICO model for defining the clinical research question  

PICO model can be defined as a format used for developing an accurate clinical research question before 

commencing a research (Eriksen & Frandsen 2018; Methley et al, 2014). PICO which means participants, 

intervention, comparator, and outcome, was used to describe this study as following; Description of 

Participants   

The participants in this study were group of individuals, selected randomly from different trials to participate in 

attesting to the effectiveness of MPTM intervention. The individuals involved were all diabetic patients 

undergoing treatment, between 8 and 75 years of age. Both males and female were included, provided they are 

being diagnosed of DM, with Hba1c > 7%.   

Type of intervention  

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Intervention in research is referred as a treatment regimen allocated to research participants with the aim of 

evaluating and assessing the effectiveness of a particular treatment/intervention (Eriksen, 2020; Higgins & 

Green, 2011). The intervention in focus for this systematic review was Mobile Phone Text Messaging Plus 

Standard Care. Comparator  

In this study, the comparator is the use of standard care only.  Amongst various studies utilised in this review, 

the comparators were stated as Usual care, Standard Care or Conventional care, but for the interest of uniformity 

in this review the comparator will be addressed as Standard Care (SC).  However, they all have the same 

meaning. Standard Care includes diabetic medications, glucose monitoring, medical advice and follow up 

appointments. Evaluation of outcome   

The primary outcome in this review, which is of great interest to the reviewer is an improved glucose control., 

which will be measured by the glycosylated haemoglobin (HbA1C). The HbA1c test signifies the average blood 

glucose level of an individual (ADA, 2014). However secondary outcomes include those outcome measures that 

will be useful to those in authority such as the decision and policy makers. The secondary outcomes could 

include: cost effectiveness of the intervention, health related quality of life, perceived social support, improved 

self-care behaviours and improved self-efficacy.  This study however focussed on the Primary Outcome. Search 

strategy  

An effective search strategy is very vital, because it helps in gathering appropriate articles needed to meet with 

the inclusion criteria (Stern et al., 2014; Wager & Wiffen, 2011), therefore a systematic and detailed search is 

essential. A well conducted search strategy gives a brief summary of the process, on how trials useful in a 

systematic review are selected (Parahoo, 2014). Boolean operators like “AND”, “OR” were utilized in 

identifying distinct studies needed in a review.   

Three major factors were employed in this review’s search strategy, which are   

• Using a reproducible method,  

• Being specific in selecting the appropriate article required to answer the study question and   

• avoiding time wastage and Sensitivity in terms of data protection. The manual and electronic methods 

were adopted in identifying articles needed for the review (Parahoo, 2014).  

A precise database known as the Cochrane database of Systematic Review (CDSR) was searched before 

conducting this systematic review, for RCTS and systematic reviews evaluating the effectiveness of MPTM 

towards maintaining glucose control amongst patients with DM. Electronic search was also thoroughly 

conducted in other useful databases which include PubMed, CINAHL, Clinical Trials.Gov, Medline, Cochrane 

Library, Embase and Database of Abstracts of Reviews of Effect (DARE). Additionally, databases such as 

BIOSIS was used in sourcing for articles shown in conferences. The Latin American and Caribbean Health 

Sciences (LILACS) was also included in the search for studies that met the criteria needed.  

Keywords such as “Text messaging”, “SMS”, and “diabetes mellitus”, “Mobile Phone text messaging and 

glucose control” were used while conducting the search strategy. The summary of search strategy was outlined 

in Table 4.1 below.  

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Table 4.1 Preliminary Study Selection  

Database 

searched   

Search Terms  Date Assessed  Number of studies 

identified by liberal 

search of database  

Time period/Language 

restriction.  

CINAHL  “Mobile Phone Text Messaging”  

AND “Diabetes Mellitus” AND  

“Randomised Controlled Trials  

10/09/2019  1  01/01/2004-01/01/2019  

No Language restriction  

PubMed  “Mobile Phone Text Messaging”  

AND “Diabetes Mellitus” AND  

“Randomised Controlled Trials”  

10/09/2019  72  01/01/2004-01/01/2019  

No Language restriction  

Medline  “Mobile Phone Text Messaging”  

AND “Diabetes Mellitus” AND  

“Randomised Controlled Trials  

10/09/2019  3  01/01/2004-01/01/2019  

No Language restriction  

Cochrane  

Central  

Register of  

Controlled  

Trials  

“Mobile Phone Text Messaging”  

AND “Diabetes Mellitus” AND  

“Randomised Controlled Trials  

10/09/2019  70  01/01/2004-01/01/2019  

No Language restriction  

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LILACS  “Mobile Phone Text Messaging”  

AND “Diabetes Mellitus” AND  

“Randomised Controlled Trials  

10/09/2019  2  01/01/2004-01/01/2019  

  

No Language restriction  

  

  

Health  

Technology  

Assessment   

“Mobile Phone Text Messaging”  

AND “Diabetes Mellitus” AND  

“Randomised Controlled Trials  

10/09/2019  100  01/01/2004-01/01/2019  

No Language restriction  

Web of  

Science  

Core  

Collection  

“Mobile Phone Text Messaging”  

AND “Diabetes Mellitus” AND  

“Randomised Controlled Trials  

10/09/2019  3  01/01/2004-01/01/2019  

No Language restriction  

Ongoing  

Studies  

“Mobile Phone Text Messaging”  

AND “Diabetes Mellitus” AND  

“Randomised Controlled Trials  

10/09/2019  3  01/01/2004-01/01/2019  

  

No Language restriction  

Other 

Sources  

“Mobile Phone Text Messaging”  

AND “Diabetes Mellitus” AND  

“Randomised Controlled Trials  

10/09/2019  3  01/01/2004-01/01/2019  

  

No Language restriction  

Total      257    

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Study selection process  

To reduce chances of selection bias, this review adopted the guidelines stated by the Centre for Review and 

Dissemination (2009) and in combination with the guidelines set by Cochrane Handbook of Systematic Review 

(Higgins & Green, 2011).  The selection criteria for this systematic review was outlined under the eligibility 

criteria. The systematic selection process first involved the electronic search for articles on the database with 

consistency in view of the research question and the eligibility criteria. Titles, abstracts and reference were 

evaluated towards selecting articles that conform with the research question. RCTTs that were not consistent 

in answering the research question were excluded from the review, following a comprehensive systematic 

screening. Studies that met the inclusion criteria were selected. Full text of the articles was recovered and used 

for the systematic selection process and future analysis. Methodological quality of the potentially included 

studies were accessed using the standards set by Consolidated Standard of Reporting Trials (CONSORT) 

statement of checklist also known as Cochrane collaboration risk of bias tool (Schulz, Altman, & Moher, 2010). 

This ensured that articles accessed as low quality of methodology were not included in the review. The 

preliminary study selection process for this systematic is presented in Figure 4.1 using a Preferred Reporting 

Items for Systematic Reviews and Meta-Analyses (PRISMA) flow diagram for systematic review.  

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Figure 4.1 Prisma Table (Moher et al., 2009). 

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Table 4. 2: Features of the included studies  

Study  Population  Intervention/Duration  Comparator  Outcome  

SMS education for the promotion 

of Diabetes Self- Management in  

low- & Middle-Income 

Countries: A randomized 

controlled trial in Egypt.   

Abaza and Marschollek, 2017.  

  

90 Type 2 DM patients 

in an Egyptian hospital 

aged 12-69 years.  

Daily text messages and 

weekly reminders for 

Diabetes care plus standard 

care for 12 weeks  

Standard Care  Glycosylated 

Haemoglobin  

Effectiveness of Text Message 

Based, Diabetes self-management 

support programme (SMS4BG): 

randomised controlled trial.  

Dobson et al., 2018  

  

366 Type 1 or Type 2 

DM patients from New 

Zealand.  

Aged 16 years   and 

above   

Tailored package of text 

messages for diabetes 

selfmanagement plus 

standard care for 9 months  

Standard Care  Glycosylated 

Haemoglobin  

An mHealth SMS-Based  

Intervention Improves Glycaemic 

Control in Hispanics with Type 2 

Diabetes.  

Fortmann et al., 2017  

  

126 Type 2 DM 

Hispanic patients in 

San Diego.  

Aged 16-75 years.  

 

Dulce digital text messages 

plus Standard care for over 6 

months  

Standard Care  Glycosylated 

Haemoglobin  

   

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A Randomised Controlled Trial 

of Sweet Talk, A Text Messaging 

System to Support Young People 

with Diabetes. Franklin et al., 

2006.  

  

126 type 1 DM 

patients in Scotland. 

Aged 8-18 years  

Conventional therapy plus 

Sweet Talk Messages for 12 

months.  

Conventional 

therapy  

Glycosylated 

Haemoglobin  

Impact of Distance Education Via  

Mobile Phone Messaging on  

Knowledge, Attitude, Practice, 

And Self Efficacy of Patients 

with Type 2 Diabetes Mellitus in 

Iran. Goodarzi et al., 2012.  

  

100 Type 2 DM  

patients in Iran,  

Aged above 30 years   

Four text messages weekly 

plus standard care for 12 

weeks  

Standard care   Glycosylated 

Haemoglobin  

A Randomised Controlled Trial 

of a Nurse Short Message Service 

by Cellular Phone for people with 

Diabetes.   

Kim, 2006  

60 Type 2 DM patients 

in South Korea. Aged 

18-50 years  

Internet based intervention 

using short message service 

(SMS) plus Standard Care for  

12 weeks  

Standard Care  Glycosylated 

Haemoglobin  

Use of Short Message Services  

(SMS) for the Management of 

Type 2 Diabetes Mellitus: A 

Randomised Controlled Trial.  

Tamban et al., 2013.   

104 diabetic patients in 

Philippines.  

Aged 19 -50 years   

3 SMS per week   plus 

standard care for 6 months  

Standard Care  Glycosylated 

Haemoglobin  

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Quality assessment  

It is important that quality of included studies is assessed when conducting a systematic review, because it 

determines if and to what extent, the results from studies were unduly influenced by the study designs selected 

(McDonagh, Peterson, Raina, Chang, & Shekelle, 2013; Smith & Noble, 2014). This was achieved by 

recording the strength and weakness of all included studies. Therefore, it is essential to adopt the use of Critical 

Appraisal Skill Program (CASP) tool in minimising bias. This tool is essential in conducting an appropriate 

methodological quality assessment of included studies (Voss & Rehfuess, 2013). This study used CASP tools 

in evaluating the methodological quality and standards of RCTS used for this study. While conducting an 

evaluation and appraisal on the methods, the quality and design included in the review and variations observed 

in the results are summarised and entered as limitations of the study as recommended (Higgins & Green, 2011). 

Table 4.3 demonstrates how each study included in the review was assessed utilising CASP tools  

Table 4.3: Methodological Quality assessment for included studies using CASP checklist tool for RCTs  

  CASP Checklist item Yes= Y. Can’t tell = C. 

No= N  

   

NAME AND  

YEAR OF  

STUDY  

PUBLICATION  

1  2  3  4  5  6                      7  8  9  10  11  

Abaza  

&Marschollek,  

2017  

Y  Y  Y  Y  Y  Y  Changes in HbA1c were 

measured. The difference in the 

HbA1c concentration between 

the patients at the intervention 

and control arm was not 

significant  

P=0.406  Y  Y  Y  

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Dobson et al., 

2018  

Y  Y  Y  N  Y  Y  Changes in HbA1c were 

measured. The reduction in 

HbA1c was significantly higher 

in the intervention arm 

compared to the Control arm.  

P=0.007  Y  Y  Y  

Fortmann et al., 

2017  

Y  Y  Y  N  Y  Y  Changes in HbA1c were 

measured. The reduction in 

HbA1c was significantly higher 

in the intervention arm 

compared to the Control arm  

P=0.03  Y  Y  Y  

Franklin et al., 

2006  

Y  Y  Y  C  N  Y  Changes in HbA1c were 

measured. There was no change 

in HbA1c between the patients 

at the intervention and control 

arm.  

P=0.99  

  

Y  Y  Y  

   
Goodarzi et al., 

2012  

Y  Y  Y  C  Y  Y  Changes in HbA1c were 

measured. The reduction in 

HbA1c was significantly 

higher in the intervention arm 

compared to the Control arm  

P=0.024  Y  Y  Y  

Kim, 2006  Y  Y  Y  C  Y  Y  Changes in HbA1c were 

measured. The reduction in 

HbA1c was significantly 

higher in the intervention arm 

compared to the Control arm  

P=0.005  Y  Y  Y  

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Tamban et al.,  

2013  

  

Y  Y  Y  Y  Y    Changes in HbA1c were 

measured. The reduction in 

HbA1c was significantly 

higher in the intervention arm 

compared to the Control arm  

P=0.04  Y  Y  Y  

Data Extraction  

Studies analysed in this review were the selected studies, whose primary outcomes measured differences in 

haemoglobin concentration (Hba1c) between participants at the intervention and the control arm. Below is a 

standardized table illustrating the studies utilised in the review. Extraction of significant data that were 

beneficial for the study was done. Features of the data extracted were the sample size, details of the participants, 

characteristics of the review and measurement of both the outcome and intervention.  

This study stated the various locations at which participants were selected, though it was randomly picked. The 

participants were from countries of various continents, namely: New Zealand, Egypt, The Philippines, South 

Korea, Scotland, Mexico, and Iran. The intervention utilised (MPTM) was briefly summarized in the table. 

The comparison between the MPTM (intervention arm and standard care (control arm) were stated as well. 

The Rev man software was utilised in entering the extracted data. This was done because Revman software 

produces a forest and funnel plot utilised in interpreting the results.  The metaanalysis was done using the 

application of a fixed effect model. Fixed effect model was used because majority of the included studies were 

quite similar especially in terms of sample size. Standard Deviation was used in measuring the estimated 

effect., since the measured outcome (HbA1c) was presented in a continuous form. Furthermore, heterogeneity 

was interpreted in the studies with the value I2 (Higgins & Green, 2011).  

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Table 4.4: Summary of Data Extraction from studies.  

STUDY  ENROLLED 

PATIENTS  

STUDY  

DURATION  

STUDY 

DESIGN  

REGION  

OF  

STUDY  

AGE OF THE 

PARTICIPANTS  

LOCATION  TYPE OF  

INTERVENTION  

HEALTH 

STATUS  

LOSS  

TO  

FOLLW  

UP  

OUTCOME 

MEASURE  

Abaza  

&Marschollek,  

2017  

90  12 Weeks  RCT  Egypt  12-69 years  University of  

Science and 

Technology 

hospital Cairo 

Egypt.  

Daily text 

messages and 

weekly reminders 

for Diabetes care 

plus standard care  

Diabetes 

Mellitus  

17  Glycosylated 

Haemoglobin  

Dobson et al., 

2018  

366  9 Months  RCT  New  

Zealand  

16  years 

 and  

above  

Primary and 

Secondary 

health centres 

across New 

Zealand.  

Tailored package 

of text messages 

for diabetes 

selfmanagement 

plus standard care  

Type 1 or  

2  

Diabetes  

Mellitus  

12  Glycosylated 

Haemoglobin  

Fortmann et al., 

2017  

126  Over 6 

Months  

RCT  San Diego  16-75 years  Federal health  

Centre, San 

Diego  

Dulce digital text 

messages plus 

Standard care  

Type 2  

Diabetes  

Mellitus  

17  Glycosylated 

Haemoglobin  

Franklin et al., 

2006  

126  12 Months  RCT  Scotland  8-18 years  Tayside Clinic 

Scotland  

Conventional 

therapy plus Sweet 

Talk  

Messages  

Type 1  

Diabetes  

Mellitus  

67  Glycosylated 

Haemoglobin  

  

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Goodarzi et al., 

2012  

100  12 Weeks  RCT  Iran  Above 30 years  Karaj  

Diabetes 

Association, 

Iran.  

Four text 

messages weekly 

plus standard care  

Type 2  

Diabetes  

Mellitus  

19  Glycosylated 

Haemoglobin  

Kim, 2006  60  12 Weeks  RCT  South 

Korea  

18-50 9years  Endocrinology 

department in 

a tertiary care  

hospital,  

South Korea  

Internet based 

intervention using 

short message 

service (SMS) 

plus Standard  

Care  

Type 2  

Diabetes  

Mellitus  

9  Glycosylated 

Haemoglobin  

Tamban et al., 

2013.  

104  6 Months  RCT  The  

Philippines  

19-50  University of 

the  

Philippines  

General  

Hospital  

3 SMS per week   

plus standard care  

Diabetes 

Mellitus  

22  Glycosylated 

Haemoglobin  

   

Table 4.5: Study outcome data  

STUDY  NOS OF PATIENTS 

THAT COMPLETED 

THE STUDY  

INTERVENTION/CONTROL  STUDY 

DESIGN  

OUTCOME (SD MEAN  

DIFFERENCE/95% CI)  

Abaza  

&Marschollek,  

2017  

73  Daily text messages and weekly reminders for 

Diabetes care plus standard care / Standard Care  

RCT  HbA1C -0.10[-1.11, 0.91]  

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Dobson et al., 

2018  

354  Tailored package of text messages for diabetes 

selfmanagement plus standard care/ Standard Care  

RCT  HbA1C -4.90[-8.22, -1.58]  

Fortmann et 

al., 2017  

109  Dulce digital text messages plus Standard care/ 

Standard Care  

RCT  HbA1C -0.90[-1.51, -0.29]  

Franklin et al., 

2006.  

59  Conventional  therapy  plus  Sweet  Talk  

Messages/Conventional Therapy  

RCT  HbA1c -0.20[-1.07, 0.67]  

Goodarzi et al., 

2012  

81  Four text messages weekly plus standard care/ 

Standard Care  

RCT  HbA1C -0.50[-1.01, 0.01]  

Kim, 2006  51  Internet based intervention using short message 

service (SMS) plus Standard Care/ Standard Care  

RCT  HbA1C -0.80[-1.32, -0.28]  

Tamban et al., 

2013  

82  3 SMS per week   plus standard care/ Standard Care  RCT  HbA1C -0.30[-0.69, 0.09]  

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Data Analysis  

Data analysis during systematic review involves the collection, summary, and combination of all included studies, 

to make informed decision based on their findings. (Higgins & Green, 2011). Data were analysed using both 

descriptive and narrative analysis, to synthesise data into an important piece of information. The analysis started 

with a descriptive summary of the included studies (Table 4.2), data extracted were inputted into a Review 

manager (Revman) 5.3 software as recommended by the Cochrane collaboration, as an essential tool for analysing 

extracted result during a systematic review for the effectiveness of public health intervention. This software was 

developed in consultation with Cochrane methodologist and reviewers to support standards and guidelines for 

systematic reviews. Therefore, it is regarded as a gold standard for analysis of data for effectiveness of a public 

health intervention (Higgins & Green, 2011).  

Data inputted into the Revman software were automatically synthesized into graphical form with statistical tools 

which include Chi-square, P-value and I2. These tools were applied to test the significance of the intervention as 

stated by the Cochrane intervention (Higgins & Green, 2011). These graphical representations were in the form 

of forest and funnel plots. Incomplete or missing data were taken into consideration when conducting this 

systematic review. This was to prevent manipulation of results which in itself is a bias. The problems associated 

with incomplete or missing data were solved by ensuring that only studies with complete data for each analysis 

were used for the analysis of outcomes of interest.  

Assessment of Heterogeneity  

While conducting this review, the assessment of heterogeneity was conducted on the studies included. All the 

studies selected in this review were thoroughly assessed of heterogeneity.Heterogeneity can be referred to as 

disimilarities in the articles  utilised in the review. These differences could be in the form of statistical, clinical or 

methodological variation (Centre for Reviews and Dissemination, 2009; Furlan, Pennick, Bombardier, & van 

Tulder, 2009; Higgins, 2013). Methodological heterogeneity  deals with variations in the methodologies utilised 

in the independent studies which includes allocation concealment, Blinding and disimilarities witnessed in the 

definition and assessment of outcomes. Statistical Heterogeneiity on the other hand recommends that the incuded 

studies are likely to lack the ability to estimate same quantity, though ststistical heterogeneity is known to evolve 

from methodological variety, Nevertheless, the above ststement fails to conclude on the ideology of  occurrence 

of variation on the  true intervention effect. Finally, Clinical Variations, are intervention effects arising as a result 

of variations in the study settings, patient’s features and the value of the intervention utilised (Centre for Reviews 

and Dissemination, 2009; Tacconelli, 2010). The Revman software was used to test for heterogeneity during data 

analysis and the reuslts were interpreted in the result section.  

Results Of The Research  

This Review evaluated 257 published articles in assessing the effectiveness of MPTM on glucose control. This 

was achieved through a comprehensive search carried out in various electronic data bases as stated in Table  

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4.1. Following the exclusion of certain studies, due to duplication and inability in meeting up the criteria designed 

for the included studies, 10 studies met the standards for the inclusion criteria, though only seven papers were 

utilised as three studies were later excluded as a result of missing data. This systematic review and meta-analysis 

were then conducted using seven studies. PRISMA flow chart was used to illustrate the process at which eligible 

studies were selected (see fig 4.1) Characteristics of the seven included studies were illustrated in table 4.2. The 

dates, at which the included studies were published ranged from 2004 to 2019. A total of 809 patients diagnosed 

with either Type1 or Type 2 Dm were included in the studies, though majority were Type 2 DM patients. This 

review had 407 patients in the experimental group and 402 at the intervention arm.  

The participants included in the study ranged between the ages of 8 and 75 years. Both male and female were 

included. Studies were carried out in different regions of the world, including Africa, Asia, Southern America and 

Europe. Out of the seven included studies, three studies had a study duration of 12 weeks(Abaza & Marschollek, 

2017; Goodarzi et al., 2012; Kim, 2007), whiles the remaining three studies had a duration of 9, 12 and 6 months 

respectively (Dobson et al., 2018; Franklin, Waller, Pagliari, & Greene, 2006; Tamban et al., 2014), except one 

study that was not very specific, however, the author stated the study duration as over 6 months (Philis-Tsimikas, 

Fortmann, Garcia, Ruiz, & Schultz, 2016). Seven studies utilised SMS as an interactive approach in terms of 

sending and receiving information to and from the patients. However, one of the studies utilised websites as well 

as SMS in sending and receiving data from participants (Kim, 2007). Two studies reported insignificant 

differences in HbA1c between the control and intervention arm (Abaza & Marschollek, 2017; Franklin et al., 

2006). Nevertheless, none of the studies reported a significant difference in HbA1c, favouring the control group.   

Based on quality assessment, two of the published included studies were at high risk for internal bias (Dobson et 

al., 2018; Philis-Tsimikas et al., 2016), however internal validity is acceptable in circumstances of low to moderate 

risk. Moreover, a study by Wood et al., (2017) sated that, in terms of assessing outcomes such as Hba1c, absence 

of blinding has little or no chances of influencing the outcome.  

Standard deviation was used in measuring the estimated effect, assessing the HbA1c concentration (primary 

outcome). As a continuous data, the analysis was done at 95% confidence interval. The seven included studies in 

the review, all had HbA1c as their primary outcome. The Meta-analysis was conducted on all the included studies, 

with the aim of producing a pooled effect. During the assessment of Heterogeneity, the Chi square test was 

(Chi2=11.67). I-squared was less than 50% (I2 = 49%), indicating less heterogeneity.  While comparing The Mean 

Differences between the control and intervention group. An overall value of Mean Difference (MD) generated 

was stated as 95% CI =-0.53 [-0.75, -0.30]. The test for overall effect was significant, which was stated as (Z=4.50; 

P<0.00001). Well detailed meta-analysis including the funnel and forest plot were displayed in Figures 5.11 and 

5.12.  

  

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Figure 5.11: Forest Plot comparing MPTM +SC with SC and HbA1c as primary outcome.  

  

  

  
  

Figure 5.12: Funnel Plot comparing MPTM +SC with SC and HbA1c as primary outcome.  

 Based on the illustration of the funnel plot demonstrated in figure 5.12., All the studies displayed on both sides 

of the plots were distributed symmetrically and captured within the precision of pooled effect however it was 

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observed that the study by Dobson et al., 2018 laid outside the symmetry of precision as it contributed the lowest 

weight to the Meta-analysis.  

A second meta-analysis was also conducted excluding studies with large sample size. A total of 407 participants 

were recorded with 200 at the experimental group and 207 at the control group. The second analysis reported the 

following results, which was stated as MD = 95% CI =-0.50 [-0.73, -0.28]. and Chi2= 4.98, I2= 0%, Z= 4.31 at P 

< 0.00001. This in essence indicates that the heterogeneity was likely high in the first meta-analysis as a result of 

high variation of sample size presented in study by Dobson et al., 2018. Due to the limited available studies that 

met the inclusion criteria, the work by Dobson et al was also utilised in carrying out the investigation for this 

review not minding the high sample size which was different from the rest of the studies.  

  

  
Figure 5.13: Forest plot comparing MPTM +SC with SC and HbA1c as primary outcome. (this diagram excludes 

the study with large sample size.  

  

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Figure 5.14: Funnel Plot comparing MPTM +SC with SC and HbA1c as primary outcome. (this diagram 

excludes the study with large sample size Risk of bias of the selected studies  

The included studies for this systematic review investigated for risk of bias using the Revman as recommended 

by the Cochrane collaboration. The assessment of risk of bias was conducted using descriptive analysis. The 

summary of the occurrence of all types of bias across the included studies are represented below (Figure 5.2) as 

produced by Revman software. The risk of bias analysis was based on the reviewer’s judgement on what was 

reported on the included studies. Based on the summary of risk of bias assessment, it was indicated in the graph, 

that blinding of personnel and participants had the greatest risk as two studies were indicated to be at high 

risk(Dobson et al., 2018; Philis-Tsimikas, Fortmann, Garcia, Ruiz, & Schultz, 2016), while 3 studies were unclear 

as the reviewer failed to mention whether blinding of participants and personnel were actually carried out during 

the course of the study(V. L. Franklin et al., 2006; Goodarzi et al., 2012; Kim, 2007). However, all the include 

studies posed low risk to selection, detection, attrition and reporting bias. As this systematic review included only 

RCTs, it was essential that all studies included were first judged for random sequence generation before other 

bias domains were investigated. There was no other type of bias detected in any of the included studies.  

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Figure 5. 1 The risk of bias summary of each study included in this systematic review based on the reviewer’s 

judgement for each bias domain.  

  

  
Figure 5. 2 The risk of bias graph. The risk of each bias domain is presented in percentage based on the reviewer’s 

judgement, across all included studies.  

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Findings of Meta-Analysis  

The first Meta-analysis involved all the included studies, while the second meta- analysis excluded a study with 

large sample size. The results obtained from the Meta-analysis were illustrated in the funnel plots and forest plots. 

Heterogeneity and P value were utilized in interpreting the results in the plot. The result from the Metaanalysis 

conducted on the studies indicated that Mobile Phone Text Messaging was effective in the maintenance of glucose 

control. A total of 809 participants were generated as the sample size from the pooled effect and were randomised 

in to MPTM +SC group and SC group. The Mean difference (MD) of the analysis indicated that the proposed 

intervention (MPTM + SC) was effective in the Maintenance of glucose control amongst Diabetic patients (MD=-

0.53, 95% CI= -0.75, -0.30, P < 0.00001).  A statically significant result was generated from the overall pooled 

effect, with a p value less than 0.05 and a confidence interval with narrow width. Hence disproving the null 

hypothesis with a prediction of the results, occurring by chance. This indicates the effectiveness of the intervention 

in reducing the Hba1c concentration amongst diabetic patients.  

All the studies with the exception of two (Abaza & Marschollek, 2017; Franklin et al., 2006) did not cross the 

line of no effect. Nevertheless, the 95% CI was continuously at the left side, hence favouring the intervention. It 

was indicated in the result, that the two studies that crossed the line of no effect individually also had a mean 

difference less than one, thereby favouring the intervention. However, both studies were statically insignificant 

with P values greater than 0.05. Irrespective of the statically insignificance of the studies, it was observed in the 

study by Franklin et al., that though there was no decrease in the Hba1C between the intervention and control 

group. Patients verbalised that the intervention improved their self-management skills and demonstrated their 

interest to continue with the intervention. Also, the study by Abaza and colleagues indicated that majority of the 

participants at the intervention arm had decreased HbaIc. Due to the statically insignificance of the result, the 

effectiveness of the study will be termed to have occurred by chance.   

The illustrated funnel plot generated from the seven studies indicated absence of publication bias. The utilised 

studies were distributed symmetrically around the pooled MD. The statically significance stated as P <0.00001, 

supports the alternate hypothesis that proposed the effectiveness of MPTM in the maintenance of glucose control 

amongst DM patients. This in essence states that the intervention helped in reducing the Hba1c level, which in 

effect improved the glucose level of the patients. Heterogeneity which was stated as 12 =49%, was suspected be 

that high as a result of higher sample size in the works of Dobson et al., when compared to the rest of the utilised 

studies.  

Heterogeneity was therefore re assessed in a second meta-analysis by excluding the study of Dobson which had 

higher sample size, than the rest of the studies. The result from the second meta-analysis indicated also statically 

significant P values with a 0 percent heterogeneity, as against the initial 49% heterogeneity. The result was stated 

as (MD= -0.50, 95% CI= (-0.73, -0.28), P < 0.0001). The funnel plot indicated symmetrical distribution of studies 

around the pooled effect hence disproving the chances of publication bias.  

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Discussion  

This systematic review focused on the work done to assist diabetic patients to manage their disease condition, 

improve behavioural and health outcomes using Mobile Phone Text Messaging (MPTM) intervention. Disease 

conditions such as diabetes requires the maintenance blood sugar levels and other related clinical and 

physiological measurements to tolerable levels through monitoring and management with consistent self-care 

routines (Jarvis, Skinner, Carey, & Davies, 2010). It was vital to note the increased use of mobile phone 

interventions in healthcare service delivery due to the fact that majority of individuals own a phone. As stated in 

the literature review, several studies have evaluated its impact as an intervention to improve various treatment 

regimens and management in healthcare delivery. These studies have demonstrated many positive trends, though 

few significant findings were reported.  

 Mobile phones as a management tool was used to enable an effective and timely flow of accurate and precise 

short information flow between the patients and the healthcare service providers. In some of the included studies, 

text messaging was used to facilitate management advice and support in between healthcare centre appointments. 

While in other studies, text messaging was used to deliver regular and timely alerts, and reminders to achieve the 

desired objective. All the included studies measured HbA1c before and after intervention and showed a significant 

decrease in HbA1c values. Results of this systematic review showed that educational interventions through the 

provision of personalized advice and support, regular and timely alerts, and reminders delivered through mobile 

phones may assist to manage diabetes and other related clinical and physiological complications thereby improve 

health outcomes. Reports from different studies suggested that that as low as 1% reduction in glycosylated 

haemoglobin can result in 37 % reduction in risk of mortality as well as micro vascular disorders (Stratton et al., 

2000). This review therefore highlighted the positive and significant evidence for rendering healthcare 

interventions that concentrated on managing diabetes through mobile phone text messaging service. The results 

of the review in line with various analysed literature (as stated on the literature review) indicated that interventions 

obtained through text messaging were very beneficial in terms of positively influencing the health outcome of 

patients.   

Summary of Effectiveness  

A study is said to be statistically significant, when the P value is less than 0.05, with a 95% confidence interval 

and a narrow width that fails to cross the line of no effect (Ellis & Steyn, 2003). The meta-analysis conducted 

proves the evidence that MPTM is statically significant in the maintenance of glucose control. The interpretation 

is that Mobile phone text messaging in addition to standard care is more effective in reducing the Hba1c levels 

among diabetic patients compared to standard diabetic care only. Based on the generated result in this review, 

results of certain studies that are in consistent with this review’s intervention were compared below.  A systematic 

review carried out by Saffari and colleagues in 2014, evaluated the effectiveness of text messaged based 

programme in maintaining glucose control amongst type 2 diabetic patients. The intervention utilised in this study 

was text message programme plus standard care.  The average age of the participants in the study was 53 years 

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.10 studies were analysed in this review. Participants at the intervention arm received text messages created in a 

tailored package called Diabetes Self-Management education. The result of the study in consistence with this 

review indicated a significant reduction of HbA1c in the experimental group, when compared to the control group. 

The overall value was stated as (SMD= -0.595; P<0.001 (Saffari et al., 2014). This indicates that the intervention 

was effective and statistically significant, as the P value was less than 0.05.  The study recorded a total of 50% 

reduction in HbA1c concentration.  

In contrast, a trial by Franklin and colleagues in 2006, included 126 young Type 1 diabetic patients recruited in 

Scotland between the ages of 8 and 18 years. Patients at the intervention arm received conventional therapy (which 

for the uniformity of this study was termed Standard Care) plus text messages form sweet talk software for 12 

months. The messages contained personalised tailored messages and precise prompts to the patient’s gender, age 

and insulin routine. There was no reduction in the HbA1c concentration at the end of the study. This was observed 

in both the intervention and control arm with a p value of 0.99 indicating that the study was not statically 

significant. However, reports from the study stated that 82% of the participants confirmed that the Sweet talk 

messaging improved their self-management system and requested to keep receiving the messages (Franklin et al., 

2006). However, factors such as sample size and study duration could have affected the significance of the result.  

The last study whose result was analysed in comparison with the result of this review was a Meta -analysis 

conducted by Liang and colleagues in 2010. The study demonstrated also the effect of Mobile phone intervention 

in the maintenance of glucose control. Unlike this review, Liang’s study engaged other forms of mobile 

technology asides text messaging. Twenty-two trials were utilised in the study with a total of 1657 participants. 

At the end of the study, it was indicated that mobile phone intervention utilised for diabetes self-management 

decreased the Hba1c level by 0.5% with a 95% confidence interval (0.3, -0.7) and a P value of 0.02(Liang et al., 

2010). The intervention in essence was effective and the p value which was less than 0.05 signified the statistical 

significance of the study.  

In comparison with Standard care alone, it is evident that addition Of MPTM to the standard diabetic care 

significantly improved the Haemoglobin concentration amongst Type 1 or Type 2 DM patients. The pooled 

analysis of various studies demonstrated the reduction of HbA1c utilizing the proposed intervention. The result 

of this review is therefore in consistent with studies in line with the effectiveness of Text messaging in improving 

health outcome.  

Application of evidence and future research  

A systematic approach was adopted in selecting and analysing the studies that demonstrated the evidence of the 

effectiveness of Mobile Phone text messaging in the maintenance of glucose control, though limitations were 

inevitable. A precise focus was taken in to consideration. Hence, the studies utilised were limited to just studies 

in which interventions were rendered solely by the means of text messaging. The application of the evidence 

provided by this systematic review is in ensuring that accurate and timely SMS reminders and updates are 

incorporated into the currently known diabetes management practices to ensure higher efficiency of selfmanaging 

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diabetes by patients. Only one study, out of all the studies, had a combination of other means of data transmission 

(internet). Thereby minimising the difficulties that would have been associated with the assessing the 

effectiveness of text messaging, when combined with other multifaced interventions.   

However, majority of the available literature on MHealth are based on complex interventions, combining text 

messaging with various forms of technology. Most of the studies in this review with the exception of the study 

by Dobson et al had comparatively low sample sizes.  Judging by the fact that none of the data from the studies 

were collected beyond twelve months, makes it difficult to draw a conclusion on the long-lasting effect of the 

proposed intervention (MPTM) in the maintenance of glucose control. Bearing in mind that Diabetes Mellitus is 

a long-term illness, there is need for studies with longer duration of follow ups. Though the included studies were 

carried out in various continents of the world, and considering the increasing rate of network coverage in addition 

to mobile phone ownership. The developing and underdeveloped nations should be well considered especially in 

terms of creating awareness on phone-based applications. However, this study made available a beneficial 

overview and also described essential gaps in knowledge encountered in this field, which values more research. 

Limitations of the review  

This review also had limitations like lack of blinding, small sample size and short duration in some of the included 

studies. The small number of significant findings could be due to the small sample sizes and short durations of 

the included studies. However, reports from studies suggested that lack of blinding has low chances of influencing 

outcomes such as haemoglobin concentration (Wood et al., 2017). The included studies did not make any note of 

power calculations, as such the overall generalizability of the data in relation to the populations is limited in scope. 

Furthermore, because the selection of studies and judgement of bias was conducted by just one reviewer, it may 

be seen as been prone to bias from the reviewer.  

Finally, one of the major limitations of this review was that the assessment outcomes report was not done at a 

more general level so as to allow for major comparison across studies. This review focused solely on HbA1c, 

which was commonly monitored by all the included studies. This was because all other related condition with 

specific factors to diabetes were not completely addressed by the included studies. As a result of this, these factors 

were not fully discussed in this systematic review.  

Conclusion  

 Mobile phone is considered as the most accessible in the world, while text messaging on the other hand, is also 

seen as the most commonly utilised means of mobile communication. Various researchers in Public Health have 

sought to explore and make the most out of the proposed communication modality.  Text messaging interventions 

were designed to provide evidence that will result to enhanced health outcome and improved health behaviour. 

The findings from the seven studies in this review illustrated that Mobile Phone Text messaging has a significant 

effect on glucose control. Furthermore, factors such as Sample size, duration of intervention and level of HbA1c 

can influence the effectiveness of an intervention. There is need for more researches to be carried out on various 

mobile application and MHealth educational means, on patients with different diseases not just DM. There is also 

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need for more researches on homogenous studies with higher sample sizes and longer duration, by so doing, there 

will be enhanced generalizability of findings. 

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