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 Table of Contents  
Year : 2018  |  Volume : 62  |  Issue : 3  |  Page : 224-226  

Effectiveness of randomized control trial of mobile phone messages on control of fasting blood glucose in patients with type-2 diabetes mellitus in a Northern State of India

1 Associate Professor, Department of Community Medicine, Dr. Rajendra Prasad Government Medical College, Kangra, Himachal Pradesh, India
2 Assistant Professor, Department of Medicine, Dr. Rajendra Prasad Government Medical College, Kangra, Himachal Pradesh, India
3 Assistant Professor, Department of Biochemistry, Dr. Rajendra Prasad Government Medical College, Kangra, Himachal Pradesh, India
4 Professor and Head, Department of Community Medicine, Dr. Radhakrishnan Government Medical College, Hamirpur, Himachal Pradesh, India

Date of Web Publication12-Sep-2018

Correspondence Address:
Dinesh Kumar
Department of Community Medicine, Dr. Rajendra Prasad Government Medical College, Kangra - 176 001, Himachal Pradesh
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/ijph.IJPH_199_17

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Limited availability of randomized control trial warranted the conduct of a present study to demonstrate the effectiveness of mobile phone-based short message services (SMSs) on reduction in mean fasting blood glucose (FBG) in patients with type-2 diabetes mellitus. A total of 955 patients were recruited from primary and secondary health-care facilities and randomized to intervention (479) and control (476) group. Messages were delivered to patients for 12 months tailoring to their recent FBG values. SMS included information to maintain the desired FBG levels and next due date for FBG assessment. Patients were statistically similar for their age, socioeconomic status, smoking, and alcohol use. After the intervention, an average FBG declined from 163.7 to 152.8 mg/dl (P = 0.019) in intervention and from 150.5 to 149.2 mg/dl (P = 0.859) in control group. Adjusted for the baseline FBG, the intervention was found to be significantly effective (odds ratio: 1.7; 95 confidence interval: 1.2–2.6).

Keywords: Blood glucose, mobile phone messages, randomized control trial, rural

How to cite this article:
Kumar D, Raina S, Sharma SB, Raina SK, Bhardwaj AK. Effectiveness of randomized control trial of mobile phone messages on control of fasting blood glucose in patients with type-2 diabetes mellitus in a Northern State of India. Indian J Public Health 2018;62:224-6

How to cite this URL:
Kumar D, Raina S, Sharma SB, Raina SK, Bhardwaj AK. Effectiveness of randomized control trial of mobile phone messages on control of fasting blood glucose in patients with type-2 diabetes mellitus in a Northern State of India. Indian J Public Health [serial online] 2018 [cited 2022 Jul 4];62:224-6. Available from:

Adherence to the prescribed treatment and lifestyle modifications are required to manage the recommended fasting blood glucose (FBG) levels in patients with type-2 diabetes mellitus (DM). Evidence has explored the role of information, communication, and technology (ICT) to improve patients' behavior and treatment compliance. Its application varies in the form of short message service (SMS) over a mobile phone, sending e-mails, automated calling, and active interaction with an informative websites.[1],[2] Reviewing the use of ICT in managing type-2 DM observed that the strength of evidence was of moderate quality due to methodological limitations such as inadequate sample size, study design, and duration of an intervention.[1],[2] Beneficial effects of SMS-based reminders were observed on the process indicators like adherence to scheduled date and time of an appointment, and also on the outcome indicators like reduction in average levels of glycosylated hemoglobin (HbA1c) and blood glucose.[3],[4],[5],[6],[7] Although review inconclusively supports for the effects of mobile phone-based interventions mainly due to the limited application of randomized control trial (RCT) and short duration of the intervention.[2] With this background, the present RCT was conducted to study the effect of individualized SMS for 12 months to improve the average FBG in patients with type-2 DM in rural settings of the northern state of India.

Himachal Pradesh is a northern state of India with a population of about 7 million (~90.0% in rural areas) and 83.0% literacy rate.[8] As per the study objective, sample size of 786 (intervention: 393 and control: 393) was calculated to detect the decline of 10.0 g/dl in average FBG in the intervention group with 1:1 ratio, 80.0% study power, and 5.0% level of significance.[9] With an expected drop out of about 20.0%, the sample size was again estimated to be 943 (~950). Hence, already diagnosed patients with type-2 DM seeks care from their respective treating physician were recruited from outpatient departments of total five health facilities of the rural area (secondary: 2; primary: 2; private: 1). Patients requiring hospital admission and without the mobile phone (self or family member) were excluded from the study. A total of 1000 patients were assessed, of which, 15 met the exclusion criteria and 30 declined to participate. Therefore, 955 study individuals were randomized, and baseline analysis was conducted (intervention: 479 and control: 476) for 6 months, followed by the intervention of 12 months (i.e., 01/07/2015–30/06/2016). The end-line assessment for 6 months was done in 852 patients (intervention: 441 and control: 411) with 11.0% drop out rate. For each facility, line list all patients were maintained during the baseline assessment. Hence, facility-wise patients were randomized into the intervention and control group by computer-generated random numbers to equally distribute the factors associated with the type of facility [Supplementary 1]. Before and after intervention the data were collected using an adapted version of the STEPS instrument (V3.1) by the World Health Organization.[10]

Group discussions and a workshop with the group of investigators (public health expert: 2, clinician: 1, laboratory:[1] with an average experience of 10 years) and a subject expert (software developer) were organized to finalize the message bank and input system for the software. It was based on the Indian Guidelines for the Management of DM developed by the Indian Council of Medical Research, New Delhi. Message bank comprised of message lines which were specific to cutoff values of selected variables such as FBG, total cholesterol (TC), body mass index (BMI), and blood pressure (BP). Thereafter, an input system was developed for software based on the cutoff value of selected variables. For every patient, if the value of the selected variable(s) observed to be more than the cutoff value, then the variable specific line was picked up from the message bank, and SMS was composed by the software. Patient-specific SMS included message lines such as name of the patient, current and ideal FBG value along with the next date of FBG assessment; current and ideal weight based on the BMI; salt restriction and advice for a brisk walk in a case of high BP; and to avoid of butter/oil-rich food items in case of high TC. The message was unidirectional (only to the patient) and in the plain English language [Table S2]. It was delivered 2 days before the due date of the FBG assessment as a reminder. It was pilot tested for a week among investigators to assess the frequency and completeness. The frequency of the SMS varied from patient to patient depending on her/his value for the input variable. On an average, each patient received messages twice in a month for 12 months. Since it was an online software triggered to the variable's value more than the cutoff, the telephone survey was carried out to ensure the receipt of messages by the patients. The information was collected on the register. Irrespective of the messages, all patients were receiving routine prescribed care (medicine and advice) from their treating physicians.

Data were analyzed with Epi-info software for statistical comparison between groups using Chi-square and Student's t-test. Regression analysis was done to derive the adjusted change in the reduction of FBG (Baseline FBG minus Endline FBG). Odds ratio (OR) as a measure of the effect along with its 95% confidence interval (95 CI) were calculated. Prior ethical approval was sought from the Institute Ethics Committee of Dr. RPGMC, Himachal Pradesh, India.

Proportions of females were more in control group, whereas for age and socioeconomic status, distribution was observed to be statistically similar in patients. The statistical similarity was also observed for a fraction and frequency of tobacco and alcohol use. Average BMI was statistically similar in both groups, but more undernourished patients were found in the intervention (5.0%) as compared to control (1.6%) group (P = 0.002). Distribution of patients with overweight and obesity was statistically similar in both groups. Like BMI, average systolic BP (SBP), average diastolic BP (DBP), and TC were without a statistically significant difference in intervention and control group. The average FBG level was significantly higher in the intervention than in the control group [Table 1].
Table 1: Characteristics of patients with type-2 diabetes mellitus in intervention and control group

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After an intervention of 12 months, the change of selected variables was assessed along with its effectiveness. Average BMI increased insignificantly in intervention, but significantly in the control group. Patients with normal BMI decreased and with obesity increased significantly in both groups, but overweight fraction changed insignificantly, but it decreased in intervention and increased in the control group. After the intervention, average SBP observed an insignificant decline, whereas, average DBP observed with a rise in both groups. The rise of DBP was insignificant in intervention but significant in the control group. As a measure of effectiveness, the average FBG decline was observed in both groups, but it was significant in intervention but insignificant in the control group. The fraction of patients with FBG >126 mg/dl decreased in both groups, but again the decline was more significant in the intervention than in the control group [Table 2].
Table 2: Change in behavior, anthropometric parameters, and fasting blood glucose after 1 year of randomized control trial in patients with type-2 diabetes mellitus in intervention and control group

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The analysis revealed a significant association between baseline and the end-line FBG in intervention (OR: 0.5; 95 CI: 0.4–0.7) and control group (OR: 0.6; 95 CI: 0.3–1.0). Logistic regression analysis was carried out, the decline in FBG as a dependent and intervention and baseline FBG as an independent variable. The unadjusted OR for intervention was 1.7 (95 CI: 1.2–2.6) and adjusted OR, with baseline FBG, was 0.2 (95 CI: 0.1–0.3). As baseline FBG observed to be a significant covariate, effect of intervention was insignificant (OR: 1.3; 95 CI: 0.8–2.3) among patients with high baseline FBG (>126 mg/dl), but was significantly effective (OR: 2.5; 95 CI: 1.4–4.5) in patients with low-baseline FBG (<126 mg/dl).

The literature supports the beneficial effect of ICT on imparting knowledge, reminding about follow-up visits for monitoring and treatment, and motivation for treatment adherence.[2],[3],[4] SMS as a strategy has varied in terms of duration, frequency, a method of function, and content of information. A systematic review of studies, only three RCT, showed an average FBG decline ranging from 5.0 to 10.0 mg/dl, which is in concurrence with the current study.[2] Thereafter, conducted RCTs reported the significant decline in average FBG and HbA1c.[5],[6],[7] The current study observed a significant decline in average FBG but with certain limitations like the inability to measure adherence to intervention and HbA1c levels. Reproducibility of the intervention entirely depends on contextual settings, like the ability to understand simple English, values, dates, and compatible handsets.


We would like to thank the Department of Health Research, Ministry of Health and Family Welfare, Government of India for providing financial assistance.

Financial support and sponsorship


Conflicts of interest

There are no conflicts of interest.

   References Top

de Jongh T, Gurol-Urganci I, Vodopivec-Jamsek V, Car J, Atun R. Mobile phone messaging for facilitating self-management of long-term illnesses. Cochrane Database Syst Rev 2012;12:CD007459.  Back to cited text no. 1
Nuti L, Turkcan A, Lawley MA, Zhang L, Sands L, McComb S. The impact of interventions on appointment and clinical outcomes for individuals with diabetes: A systematic review. BMC Health Serv Res 2015;15:355.  Back to cited text no. 2
Krishna S, Boren SA. Diabetes self-management care via cell phone: A systematic review. J Diabetes Sci Technol 2008;2:509-17.  Back to cited text no. 3
Atherton H, Sawmynaden P, Sheikh A, Majeed A, Car J. Email for clinical communication between patients/caregivers and healthcare professionals. Cochrane Database Syst Rev 2012;11:CD007978.  Back to cited text no. 4
Shariful Islam SM, Niessen LW, Ferrari U, Ali L, Seissler J, Lechner A. Effects of mobile phone SMS to improve glycemic control among patients with type 2 diabetes in Bangladesh: A prospective, parallel-group, randomized controlled trial. Diabetes Care 2015;38:e112-3.  Back to cited text no. 5
Bin Abbas B, Al Fares A, Jabbari M, El Dali A, Al Orifi F. Effect of mobile phone short text messages on glycemic control in type 2 diabetes. Int J Endocrinol Metab 2015;13:e18791.  Back to cited text no. 6
Hussein WI, Hasan K, Jaradat AA. Effectiveness of mobile phone short message service on diabetes mellitus management; the SMS-DM study. Diabetes Res Clin Pract 2011;94:e24-6.  Back to cited text no. 7
Leong KC, Chen WS, Leong KW, Mastura I, Mimi O, Sheikh MA, et al. The use of text messaging to improve attendance in primary care: A randomized controlled trial. Fam Pract 2006;23:699-705.  Back to cited text no. 8
Liew SM, Tong SF, Lee VK, Ng CJ, Leong KC, Teng CL. Text messaging reminders to reduce non-attendance in chronic disease follow-up: A clinical trial. Br J Gen Pract 2009;59:916-20.  Back to cited text no. 9
The WHO STEP wise Approach to Noncommunicable Disease Risk Factor Surveillance (STEPS). World Health Organization. Available from: [Last accessed on 2017 Aug 26].  Back to cited text no. 10


  [Table 1], [Table 2]

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