Sage Journals: Discover world-class research

Abstract

Background:

To investigate the effects of personalized DiaBetes TEXT messaging combined with Peer Support Education (DB-TEXT+ PSE) on clinical outcomes in patients with type 2 diabetes.

Methods:

An assessor-blinded, three-arm randomized controlled trial recruited 84 participants between December 2022 and July 2023. Participants were randomly assigned to a DB-TEXT + PSE group, a DB-TEXT group, or a professional education program (PEP) group. Primary outcomes included glycated hemoglobin (HbA_1c), fasting blood glucose (FBG) levels, and clinical remission rates, whereas secondary outcomes measured lipid profiles, fatigue, sleep quality, depression, and quality of life (QoL). Outcomes were assessed at baseline (T0), three months (T1), and six months (T2) postintervention.

Results:

Relative to PEP, personalized DB-TEXT + PSE and DB-TEXT alone led to significantly reduced HbA_1c levels at T1 and decreased FBG levels at T1 and T2. Type 2 diabetes remission was achieved by 35.7% and 50% of the participants in the DB-TEXT + PSE group, by 17.9% and 25% in the DB-TEXT group, and by 3.7% and 3.7% in the PEP group at T1 and T2, respectively. Relative to the PEP, DB-TEXT + PSE led to significantly reduced TC levels, diastolic blood pressure (DBP), and systolic blood pressure (SBP) and improved sleep quality and QoL over time.

Conclusions:

Personalized DB-TEXT + PSE is more effective at enhancing clinical outcomes, reducing fatigue, improving sleep quality, and improving quality of life in patients with type 2 diabetes than DB-TEXT alone and PEPs are. Educators can incorporate personalized DB-TEXT + PSE as a component of diabetes education programs and thereby integrate digital interventions and supplementary programs.

Keywords

text message peer support education type 2 diabetes diabetes clinical outcomes fatigue sleep quality

Introduction

Type 2 diabetes has become the most prevalent metabolic disorder in the world, and the incidence rate of the disorder is predicted to increase to 12.2% by 2045 for individuals aged 20 to 79 years.¹ People with diabetes and complications such as neuropathy, nephropathy, retinopathy, and cardiovascular disease² are prone to various other complications that can lead to a high financial burden³ and poor quality of life,^4,5 and these complications can cause sleep disorders,⁶ fatigue,^7,8 and psychological problems.⁹ Identifying effective strategies for managing type 2 diabetes is of clinical importance.

Diabetes self-management education and support (DSMES) programs help patients with diabetes make better health decisions and effectively engage in self-care behaviors. Such programs typically consider the clinical, educational, psychosocial, and behavioral dimensions of care.^10,11 The Association of Diabetes Care & Education Specialists (ADCES) identified seven self-care behaviors as essential components of DSMES. These behaviors comprise maintaining a healthy diet, exercising, monitoring blood sugar levels, taking prescribed medications, developing problem-solving skills, reducing risk, and engaging in healthy coping.¹² A meta-analysis reported DSMES to be effective in improving glycated hemoglobin (HbA_1c) levels, quality of life, and depression outcomes in patients with type 2 diabetes.¹³ Therefore, providing DSMES is critical for the management of type 2 diabetes.

Our previous component network meta-analysis revealed that two components—text messaging and peer support education (PSE)—were the most effective strategies within educational interventions, leading to improvements in HbA_1c levels in individuals with type 2 diabetes.¹⁴ Despite these promising insights, no randomized controlled trials (RCTs) have yet specifically investigated the effect of combining text messaging with PSE for this population. Moreover, previous studies have suggested that personalized interventions, offering tailored support based on each patient’s unique needs and preferences, may improve outcomes for individuals with diabetes.^15,16 Therefore, in the present study, we conducted a randomized controlled trial to validate the findings of our preliminary study¹⁴ and to explore the effects of personalized diabetes text messaging (DB-TEXT) combined with PSE on patients with type 2 diabetes.

Materials and Methods

Study Design

This study is an assessor-blinded, three-arm randomized controlled trial. The research was approved the Joint Institutional Review Board of the Ethical Committee of Medical Research at the Faculty of Dentistry in Jember University (No. 1738/UN25.8/KEPK/DL/2022) and Taipei Medical University (No. N202211055). We referenced the CONSORT guidelines for reporting our findings.¹⁷ The study was prospectively registered on ClinicalTrials.gov under the identifier NCT05629117.

Participants and Study Settings

We recruited participants at a diabetes management center in East Java Province between December 2022 and July 2023. We included individuals who were identified as having uncontrolled type 2 diabetes (HbA_1c level >7% in the past three months), who were aged 17 (the legal age for providing informed consent in Indonesia) to 65 years, and who had their own mobile phone. People who could not read or write Indonesian or had a diagnosis of cognitive impairment, a psychiatric disorder, or cancer prior to the study were excluded.

Sample Size Calculation

We estimated the sample size by using G Power 3.1 software,¹⁸ with an effect size of 0.3, power of 0.80, and a two-tailed α of 0.05. We calculated the effect size with reference to a previous study in which text messaging was used as the intervention and the mean changes in HbA_1c levels were considered.¹⁹ We anticipated a 20% dropout rate and determined that a sample of 84 participants would be required.

Randomization, Allocation Concealment, and Blinding

Randomization was completed using an automated online system with a 1:1:1 allocation ratio (28 per group). Sealed, numbered envelopes ensured allocation concealment. Participants were assigned to groups after baseline assessment and eligibility confirmation. Outcome assessors were blinded until the study’s end, whereas patients and therapists were aware of group allocation due to the study design.

Intervention and Control

DiaBetes TEXT Messaging Combined with Peer Support Education

Patients in the DB-TEXT + PSE group received personalized text messages tailored to Indonesian adults with type 2 diabetes. These messages, crafted by experts, addressed each patient’s preferences and status regarding healthy eating, physical activity, blood glucose monitoring, and medication use. We considered the results of a previous study²⁰ and incorporated four components of the seven self-care behaviors reported by the ADCES (ie, maintaining a healthy diet, exercising, taking medication, and monitoring blood glucose levels) into the content of the text messages.¹² The content of the text messages was developed based on previous study protocols^21,22 and in consultation with diabetes experts. Each message was no longer than 160 characters during the pilot study. The participants received personalized DB-TEXT twice weekly at approximately noon on Monday and Thursday over 12 weeks, manually delivered by our research team. Given that the participants were likely to have different dietary and physical activity preferences and to use different medications, we personalized the DB-TEXT considering their preferences and situations (Table 1).

Table 1.

The content of personalized DB-TEXT.

Contents by ADCES	Description	Reminder messages (according to their preferences)	Reminder messages (according to their preferences) in Indonesian version
Health eating	Dietary patterns characterized by eating high-quality, nutritionally dense foods in sufficient quantities to promote optimal health and well-being¹²	Good afternoon (Name). It is important to eat more vegetables at every meal in order to maintain good health and control blood glucose levels. Make sure your plate contains a variety of foods.	Selamat siang (Nama). Penting untuk makan lebih banyak sayuran setiap kali makan untuk menjaga kesehatan dan mengontrol kadar glukosa darah. Pastikan piring Anda berisi beragam makanan.
		Good afternoon (Name). Planning your meals can make a big difference. Try to include a source of lean protein, like chicken or tofu, in your dinner tonight.	Selamat siang (Nama). Merencanakan makanan Anda dapat membuat perbedaan besar. Cobalah untuk memasukkan sumber protein tanpa lemak, seperti ayam atau tahu, dalam makan malam Anda malam ini.
		Good afternoon (Name). A quick tip: eating smaller, balanced meals more frequently can help you maintain steady blood sugar levels. Consider breaking up large meals into smaller portions.	Selamat siang (Nama). Tip singkat: makan lebih sering dalam porsi kecil dan seimbang dapat membantu Anda menjaga kadar gula darah tetap stabil. Pertimbangkan untuk membagi makanan besar menjadi porsi yang lebih kecil.
		Good morning (Name). Remember to stay hydrated today. Drinking a glass of water before meals can help control your appetite and blood sugar.	Selamat pagi (Nama). Ingatlah untuk tetap terhidrasi hari ini. Minum segelas air sebelum makan dapat membantu mengontrol nafsu makan dan gula darah.
		Good afternoon (Name). During snack time! Choose a handful of nuts or a piece of fruit to keep your energy up while managing blood sugar.	Selamat pagi (Nama). Selama waktu camilan! Pilih segenggam kacang-kacangan atau sepotong buah untuk menjaga energi Anda sekaligus mengatur gula darah.
Being active	Incorporates both structured or planned exercise and unstructured physical activities, including all types, durations, and intensities of physical movement on a daily basis¹²	Good afternoon (Name). I would suggest you to do walking around 30 minutes a day at a safe place near where you live like the park.	Selamat siang (Nama). Saya menyarankan Anda untuk berjalan kaki sekitar 30 menit sehari di tempat yang aman di dekat tempat tinggal Anda seperti taman.
		Good afternoon (Name). I would suggest you to do aerobic exercise at home or at the place where you usually do it for around 30 minutes each day.	Selamat siang (Nama). Saya menyarankan Anda untuk melakukan Latihan/senam aerobik di rumah atau di tempat Anda biasanya melakukannya selama sekitar 30 menit setiap hari.
		Good afternoon (Name). I would suggest you to do cycling at the place where you usually do it for around 30 minutes each day.	Selamat siang (Nama). Saya menyarankan Anda untuk bersepeda di tempat yang biasa Anda lakukan selama sekitar 30 menit setiap hari.
		Good afternoon (Name). I would suggest you to do swimming at the swimming pool where you usually do it around 30 minutes daily.	Selamat siang (Nama). Saya menyarankan Anda untuk berenang di kolam renang di mana Anda biasanya melakukannya sekitar 30 menit setiap hari.
		Good morning (Name), it is a great day to be active! Try to fit in 30 minutes of exercise today, even in short bursts. You have got this!	Selamat pagi (Nama), ini hari yang menyenangkan untuk beraktivitas! Cobalah berolahraga selama 30 menit hari ini, bahkan dalam waktu singkat. Kamu pasti bisa melakukannya!
		Good afternoon (Name). Regular activity makes a difference! If you are able, a short walk after meals can help regulate blood sugar levels	Selamat siang (Nama). Aktivitas teratur membuat perbedaan! Jika memungkinkan, jalan kaki singkat setelah makan dapat membantu mengatur kadar gula darah
		Good afternoon (Name). Remember that even small activities like taking the stairs or parking a bit farther away can add up. Let’s keep moving!	Selamat siang (Nama). Ingatlah bahwa aktivitas kecil seperti menaiki tangga atau parkir agak jauh pun bisa menambah beban. Ayo terus bergerak!
Taking medication	A standard medication-taking behavior involves following the timing, dosage, and frequency of daily prescribed medications, as well as continuing treatment for the prescribed length of time¹²	Good afternoon (Name). Remember to take your pills on time and as recommended by your doctor.	Selamat siang (Nama). Ingatlah untuk meminum pil Anda tepat waktu dan seperti yang direkomendasikan oleh dokter Anda.
		Good afternoon (Name). Remember to inject your insulin on time and as recommended by your doctor.	Selamat siang (Nama). Ingatlah untuk menyuntikkan insulin Anda tepat waktu dan seperti yang direkomendasikan oleh dokter Anda.
		Good morning (Name). Stay on top of your routine! Taking your medications on time helps keep your energy steady and supports your goals.	Selamat pagi (Nama). Tetap ikuti rutinitas Anda! Meminum obat tepat waktu membantu menjaga energi Anda tetap stabil dan mendukung tujuan Anda.
Monitoring blood glucose level	The monitoring of blood glucose has grown beyond self-monitoring¹²	Good afternoon (Name). Measure your blood glucose level regularly as recommended by your doctor. You are doing amazing. Keep it up!	Selamat siang (Nama). Ukur kadar glukosa darah Anda secara teratur seperti yang direkomendasikan oleh dokter Anda. Anda melakukannya dengan luar biasa. Lanjutkan kerja baikmu!
Monitoring blood glucose level		Good afternoon (Name). if you are feeling unusually tired or thirsty, it might be time to check your blood glucose. Always listen to your body!	Selamat siang (Nama). Jika Anda merasa sangat lelah atau haus, mungkin inilah saatnya untuk memeriksa glukosa darah Anda. Selalu dengarkan tubuhmu!

Before the PSE was provided, peer supporter training was implemented. The peer supporter training program was conducted for 30 hours, with the content of the program adapted from previous guidelines.^23,24 The program was designed to equip peer supporters with the knowledge, skills, and strategies required to provide three key forms of peer support: (1) assistance in daily self-management, (2) social and emotional support, and (3) linkage to clinical care. Individuals were considered to be eligible to become peer supporters if they (1) had a diagnosis of type 2 diabetes, (2) were aged ≥17 years, (3) spoke Indonesian, (4) had a mobile phone, and (5) had self-reported HbA_1c ≤7.0%. They were trained to motivate participants to make positive lifestyle changes, use active listening skills, apply empowerment-based facilitation strategies, set goals, develop action plans, and solve problems. We employed formative (ie, during the training) and summative (ie, after training) assessments. To graduate from the training program, candidates were required to achieve competency in the following five domains: (1) diabetes-related knowledge, (2) empowerment-based facilitation, (3) active listening, (4) goal setting and action planning, and (5) perceived self-efficacy.^23,24 Upon successful graduation, the peer supporters received a stipend of $80 as compensation for their time investment and parking fees.

The participants were first introduced to the peer supporters at the diabetes management center, and the participants and supporters were matched on the basis of their sex and geographic location. The PSE was delivered once a week, lasting approximately 45 to 60 minutes, for a total of 12 sessions. Both the first and final sessions were conducted in-person at the management center, whereas sessions 2 through 11 were facilitated by peer supporters over the phone with their assigned partners. During the calls, the peer supporters shared their experiences and provided support related to managing diabetes regarding maintaining a healthy diet, exercising, taking medication, and monitoring blood glucose levels (Supplementary Table 1). The peer supporters were instructed to not answer questions regarding medical or clinical matters. Research assistants called each peer supporter weekly to evaluate and ensure the quality of the peer support program. Peer supporters informed the research team that all participants successfully completed all 12 sessions of the PSE program.

DiaBetes TEXT Messaging Group

The participants in DB-TEXT group received text messages twice weekly, on Monday and Thursday, over 12 weeks.

Professional Education Program Group

Health education related to diabetes management was provided to the participants in the Professional Education Program (PEP) group once per month for three months. This group received booklets regarding healthy eating and physical activity in the first month, medication adherence (eg, oral hypoglycemic agents and insulin injections) in the second month, and blood glucose monitoring in the third month.

Outcomes

Demographic and Disease Characteristics

Data on demographic and disease characteristics, including age, sex, education level, body mass index, marital status, and income level as well as current diabetes treatment, were collected using predesigned information sheets. These characteristics were reported to be associated with glycemic control in patients with type 2 diabetes.²⁵

Primary Outcomes

The primary clinical outcomes were HbA_1c and fasting blood glucose (FBG) levels at three and six months after commencement of the study. The participants were instructed to measure their FBG level after not eating or drinking anything (except water) for at least 8 hours. Type 2 diabetes remission was defined if HbA_1c levels were <6.5% for three months.²⁶

Secondary Outcomes

The participants’ total cholesterol (TC), low-density lipoprotein, high-density lipoprotein, and triglyceride levels were assessed at the diabetes management center during the study period. Systolic blood pressure (SBP) and diastolic blood pressure (DBP) were measured using a standard protocol with a standard digital sphygmomanometer. All outcomes were assessed at three and six months postintervention.

The participants’ fatigue levels were assessed using the Indonesian version of the Multidimensional Fatigue Inventory-20 (IMFI-20).²⁷ The IMFI-20 comprises 20 items and 4 subscales, namely general and physical fatigue, reduced motivation, reduced activity, and mental fatigue. Each subscale comprises four items rated on a five-point Likert scale with endpoints ranging from 1 (strongly agree) to 5 (strongly disagree). We reverse-scored 10 items with positive wording (ie, items 2, 5, 9, 10, 13, 14, 16, 17, 18, and 19). The score for each subscale (range = 4-20 points) was calculated as the sum of the scores of the items, and the total fatigue score (range = 20-100 points) was calculated as the sum of the scores of the subscales, with higher scores indicating a greater level of fatigue. The IMFI-20 had high validity and reliability (Cronbach’s α = 0.92).

Sleep quality was measured using the Pittsburgh Sleep Quality Index (PSQI). The PSQI can be used to assess self-reported sleep quality and sleep disturbance in the preceding month. The scale comprises 19 items and the following seven dimensions: (1) subjective sleep quality, (2) sleep latency, (3) sleep duration, (4) sleep efficiency, (5) sleep disturbance, (6) sleeping medication use, and (7) daytime dysfunction. The items are rated on a four-point Likert scale with endpoints ranging from 0 to 3, and the overall score ranges from 0 to 20. A score of less than five indicates favorable sleep quality.²⁸ The Indonesian version of the PSQI exhibited high validity and reliability (Cronbach’s α = 0.720).²⁹

Depression was assessed using the Beck Depression Inventory–Second Edition (BDI-II). The BDI-II comprises 21 items that are used to measure subjective depressive symptoms over the preceding two weeks.³⁰ Each item is scored on a four-point Likert scale with endpoints ranging from 0 to 3, with the total score ranging from 0 to 63.³⁰ The BDI-II includes cognitive, emotional, and somatic components.³¹ The Indonesian version of the BDI-II exhibited good convergent validity as well as high internal consistency (Cronbach’s α = 0.90).³²

Quality of life was measured using the Diabetes Quality of Life–Brief Clinical Inventory (DQoL-BCI).³³ The DQoL-BCI comprises 15 items, each of which is assessed on a five-point Likert scale (1 = very dissatisfied/all the time, 2 = moderately dissatisfied/sometimes, 3 = neither/sometimes, and 4 = moderately satisfied/very seldom). The total score of the DQoL-BCI is calculated as the average scores of all items. Total scores range from 1 to 5, with 1 indicating worse quality of life and 5 indicating better. The Indonesian version of the DQoL-BCI exhibited good reliability, with a Cronbach’s α of 0.74. The content validity index scores for the items and scale were 0.80 to 1.00 and 0.90, respectively.³⁴

Statistical Analysis

The SPSS 18.0 was used for analysis, with significance set at 0.05. We used the Kolmogorov-Smirnov to test the normality of the distribution of the data; the data were normally distributed. To compare the baseline characteristics between the groups, one-way analysis of variance was conducted for examining continuous variables, and the chi-square test was conducted for analyzing categorical variables.

We utilized intention-to-treat (ITT) principle for outcome analyses. The ITT approach was applied to mitigate potential biases caused by nonrandom dropouts. Missing data were addressed using multiple imputation, assuming the data were normally distributed and missing at random.³⁵ Linear mixed models (LMMs) were used to compare changes in the primary and secondary outcomes among the three groups at baseline (T0), three months postintervention (T1), and six months (T2) postintervention. Repeated measures analysis of variance (ANOVA) and chi-square tests were utilized to examine changes in body mass index (BMI) and type of medication over time. Because BMI and medication usage change over time, we have included adjustments for both BMI and medication type in the LMM analyses.

Type 2 diabetes remission was evaluated at three months and six months postintervention by using the chi-square test and multivariable logistic regression. The completion rate was calculated by dividing the number of respondents who completed the three-month intervention by the number of respondents who started the intervention.

Results

Participant Characteristics

A total of 84 individuals with type 2 diabetes participated in the trial and were randomly allocated to the DB-TEXT + PSE group (n = 28), DE-TEXT group (n = 28), or PEP group (n = 28). Figure 1 presents the participant recruitment flowchart reported in accordance with CONSORT guidelines. One participant in the PEP group was excluded from the study due to traffic accident-related death; 83 participants completed the intervention.

Figure 1.

Consort flow diagram of the study. DB-TEXT + PSE; DiaBetes TEXT messaging combined with Peer Support Education, DB-TEXT; diabetes text messaging, PEP; professional education program.

As presented in Table 2, the mean ages of the participants in the DB-TEXT + PSE, DE-TEXT, and PEP groups were 54.5, 53.4, and 52.8 years, respectively. More than 60% of the participants were women. We did not identify intergroup differences in the clinicodemographic characteristics of the three groups at baseline (all P > .05, Table 2).

Table 2.

Demographic and disease characteristic of the participants (n = 84).

Variables	DB-TEXT + PSE (n = 28)		DB-TEXT (n = 28)		PEP (n = 28)		P
Age	54.5	(6.3)	53.4	(7.2)	52.8	(5.4)	.76
BMI	26.3	(2.5)	25.0	(2.6)	25.2	(2.3)	.12
Diabetes duration (years)	6.2	(3.0)	6.5	(2.8)	6.0	(2.3)	.76
Female, n (%)	19	(67.9)	18	(64.3)	18	(64.3)	.95
Junior high school and above, n (%)	16	(57.1)	14	(50.0)	15	(53.6)	.60
Married, n (%)	18	(64.3)	19	(67.9)	18	(64.3)	.72
Income ≥125.22 USD/month	15	(53.6)	14	(50.0)	15	(53.6)	.95
Medications, n (%)							.81
OHA alone	2	(7.1)	2	(7.1)	1	(3.6)
OHA combined with insulin	26	(92.9)	26	(92.9)	27	(96.4)
Smoking, n (%)	6	(21.4)	5	(17.9)	6	(21.4)	.93
Charlson Comorbidity Index	1.1	(0.7)	1.0	(0.8)	0.8	(0.5)	.39

Continuous variables are presented in mean and standard deviation. Statistical analyses were provided by using one-way analysis of variance and χ² test. BMI, body mass index; USD, US dollar; SD, standard deviation; FBG, fasting blood glucose; DB-TEXT + PSE, DiaBetes TEXT messaging combined with Peer Support Education; DB-TEXT, diabetes text messaging; PEP, professional education program; OHA, oral hypoglycemic agent.

In addition, we tracked changes in BMI, as well as adjustments in medication types and dosages among participants at three and six months postintervention, to assess their progress following the intervention (Supplementary Table 2). Our findings revealed that BMI and type of medications exhibited significant changes over time among three groups (P < .05).

Supplementary Table 3 presents the primary and secondary outcomes at baseline, three months postintervention, and six months postintervention. No significant differences were observed among the three groups regarding primary and secondary outcomes at baseline, supporting the homogeneity of the study population.

Treatment Effects on Primary Outcomes

The values of HbA_1c, FBG, TC, SBP, DBP, fatigue, and quality of life significantly differed at the different time points (Supplementary Table 3, all P < .05). Table 3 presents the results of the LMM for HbA_1c and FBG. Compared with the PEP group at baseline, the DB-TEXT + PSE group exhibited significantly lower HbA_1c levels at three and six months postintervention (β = −1.14 and −1.37, respectively; both P < .001). The DB-TEXT group exhibited significantly lower HbA_1c levels at three and six months postintervention (β = −0.51 and −0.62, respectively; both P < .001) relative to the PSE group at baseline.

Table 3.

Results of linear mixed models in the effects of DB-TEXT + PSE on primary outcomes (diabetes clinical outcomes) over the study period (n = 84).

Variables	Glycated hemoglobin			Fasting blood glucose
Variables	B	SE	95% CI	B	SE	95% CI
Intercept	8.03	0.14	7.76 to 8.30	135.56	1.39	132.81 to 138.29
Three months^a	−0.20	0.19	−0.58 to −0.13	−4.74	1.96	−8.13 to −0.39
Six months^a	−0.17	0.19	−0.54 to −0.02	−4.26	1.96	−8.60 to −0.87
Groups^b
DB-TEXT + PSE	0.16	0.19	−0.23 to 0.52	−1.31	1.93	−5.11 to 2.49
DB-TEXT	0.33	0.19	−0.09 to 0.75	0.84	1.95	−2.99 to 4.67
Time × group^c
Three months × DB-TEXT + PSE	−1.14	0.27	−1.68 to −0.61	−15.07	2.74	−20.47 to −9.67
Six months × DB-TEXT + PSE	−1.37	0.27	−1.90 to −0.84	−18.72	2.75	−24.15 to −13.29
Three months × DB-TEXT	−0.51	0.27	−1.05 to −0.03	−10.37	2.75	−15.78 to −4.94
Six months × DB-TEXT	−0.62	0.27	−1.15 to −0.82	−9.99	2.75	−15.41 to −4.56

The data were analyzed using a linear mixed model, with adjustments made for BMI and type of medication.

Reference group: baseline.

Reference group: baseline (preintervention).

Reference: baseline × PEP.

SE, standard error; CI, confidence interval; DB-TEXT + PSE, DiaBetes TEXT messaging combined with Peer Support Education; DB-TEXT = diabetes text messaging.

The DB-TEXT + PSE group (β = −15.07 and −18.72, respectively; P < .001) and the DB-TEXT group (β = −10.37 and −9.99, respectively; P < .001) exhibited significantly lower FBG levels at three and six months postintervention relative to the PSE group at baseline.

Type 2 diabetes remission was achieved by 35.7% and 50.0% of the participants in the DB-TEXT + PSE group at three and six months postintervention, respectively. Only 17.9% and 25.0% of the participants in the DB-TEXT group achieved remission at three and six months postintervention, respectively, and only 3.7% and 3.7% of participants in the PEP group achieved remission at three and six months postintervention, respectively. Multivariable logistic regression revealed that the participants in the DB-TEXT + PSE group were more likely to achieve type 2 diabetes remission at three months and six months than those in the PEP group were (odds ratios = 14.44 and 26.01; 95% confidence intervals = 1.69-122.97 and 3.09-218.84, respectively). The DB-TEXT group did not achieve a significantly higher type 2 diabetes remission rate than the PEP group at three and six months postintervention (odds ratios = 5.65 and 8.67; P = .13 and .06, respectively).

Treatment Effects on Secondary Outcomes

Our results revealed that only the DB-TEXT + PSE group exhibited significantly reduced TC (β = −13.05 and −12.60, respectively), SBP (β = −5.49 and −6.39, respectively), and DBP (β = −2.15 and −2.71, respectively) at three and six months postintervention relative to the PEP group. The results also indicate a significant improvement in sleep quality from baseline to three months postintervention in the DB-TEXT + PSE group relative to the PEP group (β = −0.43). The DB-TEXT group exhibited significantly reduced SBP and DBP at three months, but not at six months, postintervention (β = −2.52 and −1.58, respectively; Supplementary Table 4).

The DB-TEXT + PSE group exhibited lower levels of fatigue (β = −5.58 and −4.51, respectively; both P < .001) and improved quality of life (β = 0.16 and 0.29, respectively; both P < .001) at three and six months postintervention relative to the PEP group at baseline. The DB-TEXT group had significantly lower levels of fatigue and significantly improved quality of life at three months, but not six months, postintervention (β = −1.35 and 0.05; P = .002 and .01, respectively; Supplementary Table 5).

Discussion

To the best of our knowledge, our study is the first randomized controlled trial to explore the effects of personalized DB-TEXT + PSE on patients with type 2 diabetes. Our findings revealed that, relative to the PEP group, the DB-TEXT + PSE group exhibited substantially improvement over time in HbA_1c levels, FBG levels, TC, SBP, DBP, fatigue, sleep quality, and quality of life. In contrast, the DB-TEXT group only exhibited reductions in HbA_1c and FBG levels at three and six months postintervention as well as reduced SBP, DBP, and fatigue at three months postintervention relative to the PEP group. Note that both intervention groups, but not the control group, exhibited downward trends in BMI and reduced diabetes-related medication dosages, which may further contribute to glycemic control.

These findings indicate that sending pertinent information and reminders through text messaging can promote a patient’s motivation to continue learning about their disease and to maintain the behaviors recommended by diabetes management guidelines.^19,36 This study demonstrated that providing personalized DB-TEXT, in which the patient is referenced by name and the content is adapted to the patient’s preferences and diabetes management status, can substantially improve glycemic control. The personalization of the messages led the participants to pay closer attention to the reminder messages they received and to maintain their diabetes care, which helped them to maintain glycemic control.

This study provides robust evidence indicating that the DB-TEXT + PSE intervention is more likely to have immediate and lasting effects on remission among patients with type 2 diabetes than DB-TEXT alone, revealing that PSE has a critical influence on the outcomes of type 2 diabetes. Peer supporters having similar life experiences to those of their matched partners (patients with type 2 diabetes) may influence the success of PSE because it leads to mutually beneficial relationships.³⁷ In the present study, by providing consistent PSE, the participants received positive support from peers with similar disease backgrounds and conditions, which made the participants more confident in continuing their diabetes care. This may be because the peer supporters shared their own strategies for effectively managing their diabetes and discussed the challenges they faced in maintaining glycemic control.

Peer support is crucial to maintaining diabetes self-management.³⁸ The participants in the DB-TEXT + PSE group had lower TC, SBP, and DBP levels at three and six months postintervention than those in the PEP group did. This finding indicates that adding a PSE component to DB-TEXT is effective for improving TC and blood pressure control in individuals with type 2 diabetes. In previous studies, PSE alone was reported to lead to similar results.^39,40 Managing blood lipid levels and blood pressure is essential for reducing the risk of diabetes complications.^41,42 The findings of the present study indicate that improving glycemic control can lead to a better lipid profile and more favorable blood pressure in people with type 2 diabetes, which is in line with the findings of previous studies.^43,44 Further studies are required to investigate the exact mechanism connecting glycemic control, lipid levels, and blood pressure among patients with type 2 diabetes.

The current study discovered that compared with PEP, personalized DB-TEXT combined with PSE led to significantly reduced fatigue levels at three and six months postintervention and improved sleep quality at three months postintervention. By contrast, compared with PEP, DB-TEXT alone only significantly reduced fatigue levels at three months postintervention. This finding supports that PSE components are crucial to managing fatigue levels and sleep quality in patients with type 2 diabetes. Glycemic control may be associated with the fatigue level and sleep quality.^27,45,46 Therefore, achieving glycemic control might improve fatigue symptoms and sleep quality in patients with type 2 diabetes.^46-48 In the present study, the personalized DB-TEXT + PSE intervention yielded greater improvement in glycemic control than the other interventions did, indicating that this intervention may improve fatigue symptoms and sleep quality.

In the present study, we further discovered that the DB-TEXT + PSE group exhibited significantly improved quality of life at three and six months postintervention relative to the PEP group. The DB-TEXT alone intervention improved quality of life at three months, but not at six months, postintervention. Patient empowerment involving diabetes self-management education and self-care behaviors is essential for enhancing quality of life among patients with type 2 diabetes.⁴⁹ Improvements in diabetes care knowledge were reported to positively affect quality of life in patients with diabetes.⁵⁰ Furthermore, providing PSE had the positive effect of improving quality of life in the patients with type 2 diabetes.⁵¹ This may be because both diabetes knowledge and psychological support, such as that from peers, were required for improving the patients’ quality of life, which may explain why DB-TEXT alone did not lead to significantly improved quality of life at six months postintervention. By combining a text messaging intervention with a peer support program, we were able to provide our participants with a comprehensive understanding of diabetes.

Strength and Limitation

The current study had several strengths. First, our study was the first RCT in evaluating the effect of DB-TEXT + PSE in improving diabetes clinical outcomes, fatigue, sleep, depression, and quality of life in patients with type 2 diabetes. Second, this study had high completion rate of the participants. In addition, this study had a number of limitations. First, since our participants were recruited from a single diabetes management center, the external validity of the study findings was restricted. Second, given the constraints of limited budget and manpower, we were unable to carry out follow-up assessments to determine the long-term effects of DB-TEXT + PSE on clinical outcomes. It is recommended that further research be undertaken to comprehensively examine the long-term impact of DB-TEXT + PSE on diabetes clinical outcomes, fatigue, sleep, depression, and quality of life among patients with type 2 diabetes.

Conclusions

Compared with DB-TEXT alone and PEP alone, personalized DB-TEXT + PSE is more likely to lead to type 2 diabetes remission and to enhance glycemic control in patients with type 2 diabetes. Furthermore, compared with PEP, personalized DB-TEXT + PSE effectively enhances TC, SBP, sleep quality, fatigue, and quality of life in patients with type 2 diabetes. Diabetes educators can incorporate personalized DB-TEXT + PSE into diabetes education programs. This approach can assist individuals with type 2 diabetes in maintaining optimal glycemic control, reducing fatigue, improving sleep quality, and improving their overall quality of life.

Supplemental Material

sj-docx-1-dst-10.1177_19322968251314501 – Supplemental material for Effects of Personalized DiaBetes TEXT Messaging Combined with Peer Support Education on Patients With Type 2 Diabetes: A Randomized Controlled Trial

Supplemental material, sj-docx-1-dst-10.1177_19322968251314501 for Effects of Personalized DiaBetes TEXT Messaging Combined with Peer Support Education on Patients With Type 2 Diabetes: A Randomized Controlled Trial by Debby Syahru Romadlon, Hui-Chuan Huang, Yu-Chi Chen, Sophia H Hu, Rudy Kurniawan, Tri Juli Edi Tarigan, Safiruddin Al Baqi, Faizul Hasan and Hsiao-Yean Chiu in Journal of Diabetes Science and Technology

Footnotes

Acknowledgements

None.

Abbreviations

ADCES, the Association of Diabetes Care & Education Specialists; BDI-II, the Beck Depression Inventory–Second Edition; BMI, body mass index; DB-TEXT, DiaBetes TEXT messaging; DB-TEXT + PSE, DiaBetes TEXT messaging combined with Peer Support Education; DBP, diastolic blood pressure; DQoL-BCI, the Diabetes Quality of Life–Brief Clinical Inventory; DSMES, Diabetes Self-Management Education and Support; FBG, fasting blood glucose; HbA_1c, glycated hemoglobin; HDL, high-density lipoprotein; IMFI-20, the Indonesian version of the Multidimensional Fatigue Inventory-20; LDL, low-density lipoprotein; LMM, linear mixed models; PSE, peer support education; PSQI, the Pittsburgh Sleep Quality Index; QoL, quality of life; RCT, randomized controlled trial; SBP, systolic blood pressure; TC, total cholesterol.

Author Contributions

DSR and H-YC designed the study. DSR, H-YC, H-CH, Y-CC, SHH, RK, TJET, SAB, and FH performed the interventions, investigations, and project administration. DSR and H-YC were responsible for data analysis, drafting, and editing the manuscript. All authors have reviewed and approved the final version of the manuscript. DSR and H-YC are accountable for the integrity of the project.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was supported by grants awarded to HYC from the National Science and Technology Council, Taiwan (NSTC 113-2628-B-038-003-MY3and NSTC 111-2314-B-038-033-MY3).

ORCID iDs

Debby Syahru Romadlon

Hsiao-Yean Chiu

Data Availability Statement

The data of this study are available from corresponding author upon request.

Supplemental Material

Supplemental material for this article is available online.

References

Sun

Saeedi

Karuranga

, et al. IDF Diabetes Atlas: global, regional and country-level diabetes prevalence estimates for 2021 and projections for 2045. Diabetes Res Clin Pract. 2022;183:109119. doi:10.1016/j.diabres.2021.109119

Zhang

Wang

, et al. Cardiovascular and all-cause mortality over a 23-year period among Chinese with newly diagnosed diabetes in the Da Qing IGT and diabetes study. Diabetes Care. 2015;38(7):1365-1371. doi:10.2337/dc14-2498

Sawhney

Shi

, et al. A systematic review of the direct economic burden of type 2 diabetes in China. Diabetes Ther. 2015;6(1):7-16. doi:10.1007/s13300-015-0096-0

Abedini

Bijari

Miri

Shakhs Emampour

Abbasi

. The quality of life of the patients with diabetes type 2 using EQ-5D-5L in Birjand. Health Qual Life Outcomes. 2020;18(1):1-9. doi:10.1186/s12955-020-1277-8

Fakhri

Abdan

Ramezanpour

Dehkordi

Sarikhani

. Systematic review and meta-analysis on quality of life in diabetic patients in Iran. Int J Prev Med. 2021;12:41. doi:10.4103/ijpvm.IJPVM_327_19

Schipper

SBJ

Van Veen

Elders

PJM

, et al. Sleep disorders in people with type 2 diabetes and associated health outcomes: a review of the literature. Diabetologia. 2021;64(11):2367-2377. doi:10.1007/s00125-021-05541-0

Chen

Liu

. Fatigue in adults with type 2 diabetes: a systematic review and meta-analysis. West J Nurs Res. 2021;43(2):172-181. doi:10.1177/0193945920938636

Romadlon

Hasan

Wiratama

Chiu

. Prevalence and risk factors of fatigue in type 1 and type 2 diabetes: a systematic review and meta-analysis. J Nurs Scholarsh. 2021;54:546-553. doi:10.1111/jnu.12763

Farooqi

Gillies

Sathanapally

, et al. A systematic review and meta-analysis to compare the prevalence of depression between people with and without Type 1 and Type 2 diabetes. Prim Care Diabetes. 2021;16:1-10. doi:10.1016/j.pcd.2021.11.001

10.

Powers

Bardsley

Cypress

, et al. Diabetes self-management education and support in type 2 diabetes: a joint position statement of the American Diabetes Association, the American Association of Diabetes Educators, and the Academy of Nutrition and Dietetics. The Diabetes Educator. 2017;43(1):40-53. doi:10.1177/0145721715588904

11.

Powers

Bardsley

Cypress

, et al. Diabetes self-management education and support in adults with type 2 diabetes: a consensus report of the American Diabetes Association, the Association of Diabetes Care & Education Specialists, the Academy of Nutrition and Dietetics, the American Academy of Family Physicians, the American Academy of PAs, the American Association of Nurse Practitioners, and the American Pharmacists Association. J Am Pharm Assoc. 2020;60(6):e1-e18. doi:10.1016/j.japh.2020.04.018

12.

Association of Diabetes Care and Education Specialists, Kolb

. An effective model of diabetes care and education: the ADCES7 Self-Care Behaviors™. Sci Diabetes Self Manag Care. 2021;47(1):30-53. doi:10.1177/0145721720978154

13.

Tanaka

Shibayama

Sugimoto

Hidaka

. Diabetes self-management education and support for adults with newly diagnosed type 2 diabetes mellitus: a systematic review and meta-analysis of randomized controlled trials. Diabetes Res Clin Pract. 2020;169:108480. doi:10.1016/j.diabres.2020.108480

14.

Romadlon

Chen

Hasan

Chiu

. Comparative efficacy of digitally assisted interventions for glycated haemoglobin levels among patients with type 2 diabetes: a systematic review and component network meta-analysis. Diabetes Obes Metab. 2023;25(11):3279-3289. doi:10.1111/dom.15227

15.

Gautier

Boitard

Michiels

Raymond

Vergez

Guedon

. Impact of personalized text messages from pharmacists on medication adherence in type 2 diabetes in France: a real-world, randomized, comparative study. Patient Educ Couns. 2021;104(9):2250-2258. doi:10.1016/j.pec.2021.02.022

16.

Cengiz

Korkmaz

. Effectiveness of a nurse-led personalized patient engagement program to promote type 2 diabetes self-management: a randomized controlled trial. Nurs Health Sci. 2023;25(4):571-584. doi:10.1111/nhs.13048

17.

Schulz

Altman

Moher

. CONSORT 2010 statement: updated guidelines for reporting parallel group randomised trials. J Pharmacol Pharmacother. 2010;1(2):100-107. doi:10.4103/0976-500X.72352

18.

Faul

Erdfelder

Buchner

Lang

. Statistical power analyses using G*Power 3.1: tests for correlation and regression analyses. Behav Res Methods. 2009;41(4):1149-1160. doi:10.3758/BRM.41.4.1149

19.

Fortmann

Gallo

Garcia

, et al. Dulce digital: an mHealth SMS-based intervention improves glycemic control in Hispanics with type 2 diabetes. Diabetes Care. 2017;40(10):1349-1355. doi:10.2337/dc17-0230

20.

Goodarzi

Ebrahimzadeh

Rabi

Saedipoor

Jafarabadi

. Impact of distance education via mobile phone text messaging on knowledge, attitude, practice and self-efficacy of patients with type 2 diabetes mellitus in Iran. J Diabetes Metab Disord. 2012;11:1-8. doi:10.1186/2251-6581-11-10

21.

Güner

Coşansu

. The effect of diabetes education and short message service reminders on metabolic control and disease management in patients with type 2 diabetes mellitus. Prim Care Diabetes. 2020;14(5):482-487. doi:10.1016/j.pcd.2020.04.007

22.

Waller

Furber

Bauman

, et al. DTEXT–text messaging intervention to improve outcomes of people with type 2 diabetes: protocol for randomised controlled trial and cost-effectiveness analysis. BMC Public Health. 2019;19:1-8. doi:10.1186/s12889-019-6550-6

23.

Tang

Funnell

Gillard

Nwankwo

Heisler

. The development of a pilot training program for peer leaders in diabetes. Diabetes Educ. 2011;37(1):67-77. doi:10.1177/0145721710387308

24.

Tang

Afshar

Elliott

Kong

Gill

. Study protocol and baseline sample characteristics: from clinic to community: using peer support as a transition model for improving long-term diabetes-related health outcomes. Contemp Clin Trials. 2019;79:104-110. doi:10.1016/j.cct.2019.02.002

25.

Mellergård

Johnsson

Eek

. Sociodemographic factors associated with HbA1c variability in type 2 diabetes: a prospective exploratory cohort study. BMC Endocr Disord. 2020;20:1-8. doi:10.1186/s12902-020-00585-6

26.

Riddle

Cefalu

Evans

, et al. Consensus report: definition and interpretation of remission in type 2 diabetes. J Clin Endocrinol Metab. 2022;107(1):1-9. doi:10.1210/clinem/dgab585

27.

Romadlon

Huang

Chen

, et al. Fatigue following type 2 diabetes: psychometric testing of the Indonesian version of the multidimensional fatigue inventory-20 and unmet fatigue-related needs. PLoS ONE. 2022;17(11):e0278165. doi:10.1371/journal.pone.0278165

28.

Buysse

Reynolds

3rd Monk

Berman

Kupfer

. The Pittsburgh sleep quality index: a new instrument for psychiatric practice and research. Psychiatry Res. 1989;28(2):193-213. doi:10.1016/0165-1781(89)90047-4

29.

Setyowati

Chung

. Validity and reliability of the Indonesian version of the Pittsburgh sleep quality index in adolescents. Int J Nurs Pract. 2021;27(5):e12856. doi:10.1111/ijn.12856

30.

Beck

Steer

Brown

. Beck depression inventory (BDI-II). Vol. 10. London: Pearson; 1996.

31.

Beck

Steer

Brown

Van der Does

. BDI-II-NL Handleiding [BDI-II-Dutch Manual]. Lisse: Psychological Corporation; 2002.

32.

Ginting

Näring

Van Der Veld

Srisayekti

Becker

. Validating the Beck Depression Inventory-II in Indonesia’s general population and coronary heart disease patients. Int J Clin Health Psychol. 2013;13(3):235-242. doi:10.1016/S1697-2600(13)70028-0

33.

Burroughs

Desikan

Waterman

Gilin

McGill

. Development and validation of the diabetes quality of life brief clinical inventory. Diabetes Spectrum. 2004;17(1):41-49. doi:10.2337/diaspect.17.1.41

34.

Irianti

Wicaksana

Pangastuti

. Validity and reliability test of the Indonesian version for diabetes quality of life-brief clinical inventory. Indian J Public Health. 2021;12(1):435. doi:10.37506/ijphrd.v12i1.13885

35.

Jakobsen

Gluud

Wetterslev Winkel

. When and how should multiple imputation be used for handling missing data in randomised clinical trials—a practical guide with flowcharts. BMC Med Res Methodol. 2017;17:1-10. doi:10.1186/s12874-017-0442-1

36.

Abaza

Marschollek

. SMS education for the promotion of diabetes self-management in low & middle income countries: a pilot randomized controlled trial in Egypt. BMC Public Health. 2017;17(1):1-19. doi:10.1186/s12889-017-4973-5

37.

Dennis

. Peer support within a health care context: a concept analysis. Int J Nurs Stud. 2003;40(3):321-332. doi:10.1016/S0020-7489(02)00092-5

38.

Liang

Jia

Zhou

, et al. The effectiveness of peer support on self-efficacy and self-management in people with type 2 diabetes: a meta-analysis. Patient Educ Couns. 2021;104(4):760-769. doi:10.1016/j.pec.2020.11.011

39.

Patil

Ruppar

Koopman

, et al. Effect of peer support interventions on cardiovascular disease risk factors in adults with diabetes: a systematic review and meta-analysis. BMC Public Health. 2018;18:1-10. doi:10.1186/s12889-018-5326-8

40.

Zhao

Zhang

. The role of peer support education model in management of glucose and lipid levels in patients with type 2 diabetes mellitus in Chinese adults. J Diabetes Res. 2019;2019:5634030. doi:10.1155/2019/5634030

41.

UK, Prospective Diabetes Study (UKPDS) Group. Intensive blood-glucose control with sulphonylureas or insulin compared with conventional treatment and risk of complications in patients with type 2 diabetes (UKPDS 33). Lancet. 1998;352(9131):837-853. doi:10.1016/S0140-6736(98)07019-6

42.

UK, Prospective Diabetes Study Group. Tight blood pressure control and risk of macrovascular and microvascular complications in type 2 diabetes: UKPDS 38. BMJ. 1998;317(7160):703-713. doi:10.1136/bmj.317.7160.703

43.

Khan

Sobki

Khan

. Association between glycaemic control and serum lipids profile in type 2 diabetic patients: HbA1c predicts dyslipidaemia. Clin Exp Med. 2007;7(1):24-29. doi:10.1007/s10238-007-0121-3

44.

Yoda

Inaba

Hamamoto

, et al. Association between glycemic control and morning blood pressure surge with vascular endothelial dysfunction in type 2 diabetic patients. Diabetes Care. 2014;37(3):644-650. doi:10.2337/dc13-1102

45.

Fritschi

Quinn

. Fatigue in patients with diabetes: a review. J Psychosom Res. 2010;69(1):33-41. doi:10.1016/j.jpsychores.2010.01.021

46.

Sakamoto

Yamakawa

Takahashi

, et al. Association of usual sleep quality and glycemic control in type 2 diabetesin Japanese: a cross sectional study. PLoS ONE. 2018;13(1):e0191771. doi:10.1371/journal.pone.0191771

47.

Fritschi

Park

Quinn

Collins

. Real-time associations between glucose levels and fatigue in type 2 diabetes: sex and time effects. Biol Res Nurs. 2020;22(2):197-204. doi:10.1177/1099800419898002

48.

Seo

Hahm

Kim

Choi

. Factors affecting fatigue in patients with type II diabetes mellitus in Korea. Asian Nurs Res (Korean Soc Nurs Sci). 2015;9(1):60-64. doi:10.1016/j.anr.2014.09.004

49.

Alaofè

Hounkpatin

Djrolo

Ehiri

Rosales

. Factors associated with quality of life in patients with type 2 diabetes of South Benin: a cross-sectional study. Int J Environ Res Public Health. 2022;19(4):2360. doi:10.3390/ijerph19042360

50.

Tamornpark

Utsaha

Apidechkul

Panklang

Yeemard

Srichan

. Quality of life and factors associated with a good quality of life among diabetes mellitus patients in northern Thailand. Health Qual Life Outcomes. 2022;20(1):81. doi:10.1186/s12955-022-01986-y

51.

Kong

Yang

Cui

. The effectiveness of peer support on self-efficacy and quality of life in adults with type 2 diabetes: a systematic review and meta-analysis. J Adv Nurs. 2019;75(4):711-722. doi:10.1111/jan.13870

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

0.05 MB