Effectiveness of a Lifestyle Improvement Support App in Combination with a Wearable Device in Japanese People with Type 2 Diabetes Mellitus: STEP-DM Study
Although the use of application (app)s and wearable devices supporting diabetes treatment has spread rapidly in recent years, evidence of their impact, especially in combination of them, is limited. TOMOCO™ is a lifestyle improvement support app that features interactive virtual conversations according to the programmed algorithm guiding users toward their goals of lifestyle improvement. We hypothesized that TOMOCO™ in combination with Fitbit, which accurately tracks users’ activity level, would encourage people with type 2 diabetes mellitus (T2DM) to change their lifestyles and improve their glycated hemoglobin (HbA1c) levels without changes in conventional therapy. Thus, we performed the present study to explore the effectiveness of this combination in Japanese participants with T2DM who had not achieved their glycemic targets.
Methods
In this single-arm exploratory study, participants with T2DM used the TOMOCO™ and Fitbit in addition to the conventional diet/exercise therapy and anti-diabetic drug for 12 weeks. They were provided with feedback/advice by health care providers based on the TOMOCO™ and Fitbit records. The primary endpoint was the change in HbA1c from baseline to the end of the observation period. Data were expressed as mean ± standard deviation.
Results
Fifty-nine (96.7%) of the 61 participants (male, 42 [71.2%]; age, 60.1 ± 8.7 years; HbA1c level, 7.48 ± 0.37% at screening) completed the study. At the end of the observation period, the HbA1c was significantly reduced (− 0.41 ± 0.41%, p < 0.001). This trend was consistent across the preselected patient characteristics, including sex, age, and body mass index. However, it was more pronounced in the participants with earlier stages of behavioral changes defined by the transtheoretical model at baseline.
Conclusions
The unique features of TOMOCO™ in combination with Fitbit, together with conventional therapy, may promote a healthy lifestyle and thus contribute to improving HbA1c in people with T2DM.
Prior presentation: The materials in this manuscript were presented at the 66th Annual Meeting of the Japan Diabetes Society, Kagoshima, Japan, May 11–13, 2023; the 83rd Scientific Sessions of the American Diabetes Association, San Diego, CA, June 23–26, 2023; and the IDF-WPR Congress 2023 / 15th Scientific Meeting of AASD, Kyoto, Japan, July 21–23, 2023.
Key Summary Points
Why carry out this study?
Digital tools such as application (app)s and wearable devices are increasingly being used to support self-management in people with type 2 diabetes mellitus (T2DM). However, more research is needed to determine whether such tools are effective (particularly in combination of apps and wearable devices).
TOMOCO™ is a lifestyle improvement support app developed to support lifestyle changes. It is considered useful for self-management of people with T2DM who need to make lifestyle changes.
This single-arm exploratory study investigated the effectiveness of the combined use of TOMOCO™ and Fitbit in addition to conventional therapy in participants with T2DM who had not achieved their glycemic targets.
What was learned from the study?
There was a significant reduction in glycated hemoglobin (HbA1c) levels from baseline to the end of the 12-week observation period, particularly for participants with less engagement in behavioral changes at baseline.
Both HbA1c levels and participant responses to the intervention suggested that TOMOCO™ in combination with Fitbit was effective and user-friendly and could promote behavioral change toward lifestyle improvement for T2DM treatment.
Introduction
Despite the availability of various therapeutic agents for type 2 diabetes mellitus (T2DM), about half of the affected patients in Japan fail to achieve their glycemic targets [1, 2]. The therapeutic effects of these agents have been reportedly attenuated by less engagement in diet and exercise therapy [3, 4]. Different strategies aimed at maintaining self-management, including diet and exercise therapies, have been investigated; however, given that many people still do not achieve their treatment goals, new strategies are clearly needed [5‐7].
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The use of digital tools such as smartphone application (app)s and wearable devices supporting diabetes treatment has spread rapidly in recent years [8‐11]. These tools have shown potential to be useful in diabetes treatment, supporting the daily self-management of people with T2DM and ensuring successful treatment. Nevertheless, they have some limitations, such as the low retention rate, information technology literacy of users, and technical issues (e.g., data extraction) [11‐15].
TOMOCO™ is a lifestyle improvement support app developed by Mitsubishi Tanabe Pharma Corporation (Osaka, Japan) and Habitus Care Inc. (Tokyo, Japan). It has been used by the Japanese Health Insurance Association as a tool for providing specific health guidance to people who are at high risk of lifestyle-related diseases, e.g., diabetes, hypertension, dyslipidemia etc., which can lead to serious cardiovascular diseases. The targets of this guidance are identified by abnormalities in metabolic parameters such as waist circumference, body mass index, blood glucose levels, lipid concentrations, blood pressure, and smoking habits at their annual health checkups [16]. In the present study, we used TOMOCO™ as a self-management tool in the treatment of participants with T2DM. We also adopted the Fitbit, which is a wearable device promoted by Google LLC (Mountain View, CA, USA), to more accurately understand participants’ activity status. We hypothesized that TOMOCO™ in combination with the Fitbit would encourage people with T2DM to improve their lifestyles and that as a result, their glycated hemoglobin (HbA1c) levels would improve without changes in conventional therapy. Thus, we carried out the present study (STEP-DM: Effect of Lifestyle Management with a Wearable Device [Fitbit] and a Mobile App [TOMOCO] on Glycemic Control in Medicated Patients with Insufficiently Controlled Type 2 Diabetes Mellitus) to elucidate the effectiveness of adding the TOMOCO™-Fitbit combination to conventional therapy in Japanese people with T2DM who had not achieved their glycemic targets.
Methods
Study Design and Participants
We conducted a single-arm exploratory study at Kunisaki Makoto Clinic in Fukuoka, Japan. We recruited people with T2DM who had not achieved their glycemic targets, defined as HbA1c levels of 7.0% to < 8.5% at screening (SCR) that did not improve or improved by ≤ 0.2% during the 12 weeks before SCR despite conventional guidance on lifestyle changes, including diet and exercise therapies, and treatment with anti-diabetic drugs for at least 12 weeks. A full list of the eligibility criteria is provided in Supplementary Table S1.
All procedures were conducted in accordance with the Declaration of Helsinki and the local regulations. All participants gave written informed consent. Site monitoring was conducted by EPS Corporation (Tokyo, Japan). Since the study site did not have its own ethical review body, this study was reviewed and approved by the certified ethical review committee established by Saga Memorial Hospital (ID. 16000061). The study was registered in the Japan Registry of Clinical Trials (jRCT ID: 1070220007).
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Procedures
All participants used the TOMOCO™ app and the Fitbit device in addition to conventional diet/exercise therapy and anti-diabetic drug for the 12 weeks of observation period. The conventional therapy, including anti-diabetic drugs, remained unchanged throughout the observation period. Participants visited the study site every 4 weeks to undergo blood tests including HbA1c, body weight measurements, and received feedback/advice from health care providers (HCPs) based on the TOMOCO™ and Fitbit records (Supplementary Fig. S1).
Additionally, a questionnaire survey was conducted at baseline and at 12 weeks. At baseline, the participants were asked about their awareness of the importance of diet and exercise therapy in diabetes treatment and how they were implementing it. At 12 weeks, they were asked about how helpful TOMOCO™ and Fitbit were for diet and exercise therapy. A full list of the questionnaire and answer options are provided in Supplementary Table S2.
The primary endpoint was the mean change in the HbA1c levels from baseline to 12 weeks, and the secondary endpoints were the mean change in body weight from baseline to 12 weeks and the response to the questionnaire.
Lifestyle Improvement Support App
The TOMOCO™ lifestyle improvement support app is specifically designed to support lifestyle changes in people who are at high risk of lifestyle-related diseases, e.g., diabetes, hypertension, dyslipidemia and cardiovascular diseases, identified by abnormalities in their metabolic parameters including waist circumference, body mass index, blood glucose levels, lipid concentrations, blood pressure, and smoking habits. The system consists of a smartphone app (TOMOCO™ app) and a web-based interface (TOMOCO™ web system). The TOMOCO™ app features interactive virtual characters called “concierges” who accompany the study participants toward their goals for lifestyle improvement. The participants input their daily records, such as diet, exercise, and medications, and the concierge then sends encouraging messages according to the programmed algorithm and gives rewards such as items that can be used in the app based on the participant’s achievements on a daily basis. In addition, the points awarded according to the achievements compared with other TOMOCO™ users are displayed on each participant’s app in a ranking format (Supplementary Figs. S2 and S3). The TOMOCO™ web system was synchronized with the TOMOCO™ app and monitored by the HCPs in the present study. It was used in the participants’ consultations during their study visits (Fig. 1).
Fig. 1
Combined use of a lifestyle improvement support app (TOMOCO™) and a wearable device (Fitbit). HCP health care provider, TTM transtheoretical model
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The TOMOCO™ app also assessed the participant’s stages of behavioral changes at baseline using a transtheoretical model (TTM), which is scored in five stages: 1, precontemplation; 2, contemplation; 3, preparation; 4, action; and 5, maintenance. People in stages 1, 2, or 3 were considered to be unaware of the need to improve their lives or to have an understanding of the need but have not yet taken action [17, 18].
Wearable Device
The Fitbit Charge 5 activity tracker was used in this study. This device tracked physical activities, such as step count, heart rate, sleep hours, and sleep quality, throughout the entire study period. The participants were instructed to wear the Fitbit constantly, except when charging the battery. The Fitbit-tracked step count data, which accurately reflect physical activity, were transferred to the TOMOCO™ in this study (Fig. 1).
Data Collection
The TOMOCO™ data were extracted by Habitus Care Inc., and the Fitbit data were collected via Selfbase™ (Tech Doctor Inc., Tokyo, Japan). Other data were collected using an electronic data capture system (Marvin version 2.6.16; XClinical GmbH, Munich, Germany). All data were sent to the data center (INTAGE Healthcare Inc., Tokyo, Japan) for analysis.
Sample Size Calculation
The sample size was calculated for the change in the HbA1c levels from baseline. Based on previous studies [19, 20], we estimated a mean ± standard deviation (SD) change in the HbA1c levels from baseline to 12 weeks of 0.3 ± 0.7%. For a two-sided significance level of 5%, a sample size of 45 would provide a power of 80% for the analysis (paired t test). Therefore, we set a target of 60 enrolled participants to account for potential dropouts or failure to obtain values for evaluation.
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Statistical Analysis
We analyzed the results in the full analysis set (FAS), which was defined as the group of participants who started using the TOMOCO™ app in combination with Fitbit after enrollment and who had HbA1c data at baseline and 12 weeks.
The percentage of days during which the TOMOCO™ app was active (days of activation at least once a day / days of observation × 100) and the Fitbit-wearing time per day (hours) are expressed as median, range, and interquartile range to show usage levels. Unless otherwise noted, values are expressed as mean ± SD or median and range. The percentage of responses to the questionnaire was calculated. Pre- and post-intervention data were compared using paired t tests. Subgroup analyses were carried out with stratification by preselected participant characteristics acquired at SCR and the TTM score at baseline, and the results were compared in an inter-category manner using Student’s t test or analysis of variance. A significance level of 5% was used for all tests. No adjustment for multiplicity was performed because this was an exploratory study. Statistical analysis was conducted using SAS Release 9.4 TS Level 1 M5, 64bit (SAS Institute Inc., Cary, NC, USA).
Results
Study Participants, Characteristics, and Baseline TTM Score
Participant recruitment began in April 2022, and observations were completed in December 2022. Sixty-one participants were enrolled, 59 of whom completed the study and were included in the FAS (Fig. 2). The participants’ background characteristics at SCR are listed in Table 1. Among the FAS population, 42 (71.2%) participants were men, the mean age was 60.1 ± 8.7 years, the mean body mass index was 25.16 ± 3.72 kg/m2, and the mean HbA1c levels at SCR was 7.48 ± 0.37%. Among the 59 participants, 32 had a baseline TTM score of 1, 2, or 3 (i.e., behavioral stages in precontemplation, contemplation, or preparation), and 27 had a baseline TTM score of 4 or 5 (i.e., behavioral stages in action or maintenance). The distribution is listed in Supplementary Table S3.
Fig. 2
Participant flowchart. FAS full analysis set (participants who started using the TOMOCO™ app and Fitbit after enrollment and who had glycated hemoglobin levels at baseline and 12 weeks)
Difference in HbA1c (%) between 12 weeks before SCR and at SCR, n
59
Mean ± SD
0.09 ± 0.26
Number of anti-diabetic agents, n
59
1
6 (10.2%)
2
26 (44.1%)
3
19 (32.2%)
4
8 (13.6%)
Use of anti-diabetic agent category at SCR, n
59
Metformin
45 (76.3%)
DPP-4 inhibitors
40 (67.8%)
SGLT2 inhibitors
32 (54.2%)
Insulins
13 (22.0%)
Sulfonylureas
5 (8.5%)
GLP-1 receptor agonists
4 (6.8%)
Glinides
3 (5.1%)
Thiazolidine
2 (3.4%)
Imeglimin
1 (1.7%)
BMI body mass index, CV cardiovascular, DPP-4 dipeptidyl peptidase-4, GLP-1 glucagon-like peptide-1, HbAlc glycated hemoglobin, SCR screening, SD standard deviation, SGLT2 sodium-glucose cotransporter 2, T2DM type 2 diabetes mellitus
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TOMOCO™ App and Fitbit Usage
TOMOCO™ app and Fitbit usage during the study period was evaluated according to the percentage of days during which the TOMOCO™ app was activated and the length of time for which the Fitbit was worn. The median and the range of percentage of days during which the TOMOCO™ app was activated was 100 (32.94−100)% (Fig. 3A). The median and the range of Fitbit-wearing time during the entire study period was 21.9 (8.7−23.6) h/day (Fig. 3B).
Fig. 3
TOMOCO™ app and Fitbit usage. A Percentage of days during which the TOMOCO™ app was active (days of activation at least once a day/days of observation × 100). B Fitbit-wearing time per day (hours). Data are expressed as boxplots. W weeks
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Primary and Secondary Outcomes
The mean HbA1c levels were significantly decreased at the end of the study period from baseline (− 0.41 ± 0.41%, p < 0.001) (Fig. 4A). In addition, 48 of 59 (81.4%) participants had HbA1c levels below baseline at 12 weeks (Fig. 4B). Regarding the categorical distribution of the HbA1c levels, 3.4% of participants had an HbA1c level of < 7.0% at baseline, and this increased to 30.5% at 12 weeks (Supplementary Fig. S4). The mean body weight was also decreased (− 0.88 ± 1.58 kg, p < 0.001) (Fig. 5A), with 43 of the 59 (72.9%) participants showing a reduced body weight from baseline (Fig. 5B).
Fig. 4
Changes in HbA1c levels. A Change from baseline (%). * − 0.41 ± 0.41 (p < 0.001, paired t test). Data are expressed as mean ± SD. B Individual change from baseline at 12 weeks. Data are expressed as waterfall plots. HbA1c glycated hemoglobin, SD standard deviation
Fig. 5
Changes in body weight. A Change from baseline (kg). * − 0.88 ± 1.58 (p < 0.001, paired t test). Data are expressed as mean ± SD. B Individual change from baseline at 12 weeks. Data are expressed as waterfall plots. SD standard deviation
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The responses to the questionnaire survey conducted at baseline and 12 weeks are shown in Supplementary Figures S5 and S6. Although 98.3% and 100% of the participants agreed at baseline that diet and exercise, respectively, were important for diabetes treatment (Q2 and Q4), more than half of the participants answered, “not much” or “not at all” (Q3 and Q5) in their implementation (Supplementary Fig. S5). After 12 weeks, 98.3% and 94.9% of the participants answered that the TOMOCO™ app and Fitbit were “helpful” or “somewhat helpful,” respectively, for the self-management of their diabetes treatment (Q1 and Q6). Furthermore, 79.6–94.9% of the participants responded that they were “motivated” or “slightly more motivated” to follow their diet and exercise therapies by TOMOCO™ (Q2 and Q3) and the Fitbit (Q7 and Q8) (Supplementary Fig. S6).
Subgroup Analyses
We analyzed the changes in the HbA1c levels from baseline in subgroups stratified by preselected participant background characteristics and baseline TTM scores. The results were consistent across the preselected background characteristics, with no significant difference among the subgroups (Table 2). However, the change in the HbA1c levels from baseline was more pronounced in participants with lower baseline TTM scores (1, 2, or 3) than in those with higher scores (4 or 5) (p for interaction = 0.038) (Table 3).
Table 2
Actual values and changes from baseline for HbA1c stratified by participant background characteristics
Background characteristics
Category
n
HbA1c (%), mean ± SD
p valuea
Baseline
12 weeks
Change from baseline
Paired t test
Student’s t test
–
All
59
7.57 ± 0.42
7.16 ± 0.47
− 0.41 ± 0.41
< 0.001
–
Sex
Male
42
7.53 ± 0.39
7.15 ± 0.48
− 0.38 ± 0.44
< 0.001
0.482
Female
17
7.66 ± 0.50
7.19 ± 0.44
− 0.46 ± 0.32
< 0.001
Age (years)
< 65
36
7.56 ± 0.44
7.16 ± 0.51
− 0.40 ± 0.48
< 0.001
0.957
≥ 65
23
7.57 ± 0.39
7.17 ± 0.41
− 0.41 ± 0.27
< 0.001
BMI (kg/m2)
< 25
31
7.60 ± 0.41
7.20 ± 0.46
− 0.40 ± 0.31
< 0.001
0.889
≥ 25
27
7.54 ± 0.44
7.13 ± 0.48
− 0.42 ± 0.51
< 0.001
Cardiovascular diseases
With
12
7.48 ± 0.45
7.09 ± 0.41
− 0.39 ± 0.23
< 0.001
0.900
Without
47
7.59 ± 0.41
7.18 ± 0.48
− 0.41 ± 0.45
< 0.001
Bone and joint diseases
With
4
7.58 ± 0.43
6.93 ± 0.21
− 0.65 ± 0.31
0.025
0.219
Without
55
7.57 ± 0.42
7.18 ± 0.48
− 0.39 ± 0.41
< 0.001
Duration of T2DM (years)
< 5
19
7.37 ± 0.38
6.98 ± 0.44
− 0.39 ± 0.49
0.003
0.842
≥ 5
40
7.66 ± 0.41
7.25 ± 0.46
− 0.41 ± 0.37
< 0.001
HbA1c (%) at SCR
< 8.0%
52
7.48 ± 0.37
7.10 ± 0.42
− 0.38 ± 0.41
< 0.001
0.217
≥ 8.0%
7
8.19 ± 0.21
7.60 ± 0.57
− 0.59 ± 0.39
0.008
Difference in HbA1c (%) between 12 weeks before SCR and SCR
< 0
22
7.44 ± 0.39
7.14 ± 0.42
− 0.30 ± 0.28
< 0.001
0.130
≥ 0
37
7.64 ± 0.42
7.18 ± 0.50
− 0.47 ± 0.46
< 0.001
Number of anti-diabetic agents
1
6
7.60 ± 0.49
7.43 ± 0.83
− 0.17 ± 0.56
0.502
0.188
2
26
7.52 ± 0.47
7.07 ± 0.43
− 0.45 ± 0.44
< 0.001
3
19
7.62 ± 0.36
7.13 ± 0.34
− 0.49 ± 0.35
< 0.001
4
8
7.58 ± 0.40
7.35 ± 0.44
− 0.23 ± 0.21
0.020
BMI body mass index, HbA1c glycated hemoglobin, SCR screening, SD standard deviation, T2DM type 2 diabetes mellitus
ap values: Before and after comparisons using paired t tests and inter-category comparisons using Student’s t test or analysis of variance
Table 3
Actual values and changes from baseline for HbA1c stratified by behavior change stage at baseline
Category
n
HbA1c (%), mean ± SD
p valuea
Baseline
12 weeks
Change from baseline
Paired t test
Student’s t test
Change in TTMb
1 or 2 or 3
32
7.65 ± 0.42
7.15 ± 0.40
− 0.51 ± 0.42
< 0.001
0.038
4 or 5
27
7.46 ± 0.41
7.18 ± 0.54
− 0.29 ± 0.36
< 0.001
HbA1c glycated hemoglobin, SD standard deviation, TTM transtheoretical model
ap values: Before and after comparisons using paired t tests and inter-category comparisons using Student’s t test
In this study, in participants who had T2DM with glycemic management that did not sufficiently improve during the previous 12 weeks, the HbA1c levels significantly improved after using the TOMOCO™ app in combination with Fitbit for 12 weeks, in addition to conventional therapy, and this trend was consistent across participants with different background characteristics. However, the effectiveness of this strategy was more pronounced in participants who were in the earlier stages of behavioral change at baseline. In other words, the use of the TOMOCO™ in combination with Fitbit appeared to offer a useful adjunct tool to conventional diabetes treatment and was highly effective in people who had not yet made the behavioral changes required to improve their lifestyle. To the best of our knowledge, this study provides the first evidence of the effectiveness of a lifestyle improvement support app (TOMOCO™) in combination with a wearable device (Fitbit) in people with T2DM who had not achieved their glycemic targets.
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The effectiveness of digital tools such as apps and wearable devices has also been recognized in several other studies, but many people discontinue using them during self-management of chronic diseases including T2DM [11‐15]. Although the present study had a short observation period of 12 weeks, there was no noticeable decrease in the frequency of use except for a few participants, and only two participants discontinued the study. These results indicate that the TOMOCO™ in combination with Fitbit, in addition to conventional therapy, was user-friendly.
The goal of diabetes treatment is to prevent the onset and progression of its complications and enable people with diabetes to maintain their quality of life and life expectancy at a level comparable to those without the ailment [21]. A healthy lifestyle has been shown to be associated with reduced long-term adverse outcomes in people with T2DM [22‐24]. In other words, the success of diabetes treatment relies on people changing their behavior to improve their lifestyle and maintain their engagement with diabetes treatment [3‐7]. According to the questionnaire survey conducted at baseline, although most participants understood the importance of diet/exercise therapy for diabetes treatment, more than half of them did not sufficiently adhere to such therapy. This highlights the need to improve glycemic management through adequate engagement in lifestyle change. Use of the TOMOCO™ app in combination with Fitbit for 12 weeks significantly improved the HbA1c levels in most participants in the current study, and most participants indicated in the questionnaire that the TOMOCO™ app and Fitbit motivated them to engage with diet and exercise therapies. These results suggest that TOMOCO™ in combination with Fitbit was helpful to participants who are required to make lifestyle changes for diabetes management.
This study also explored whether the use of TOMOCO™ and Fitbit could be effective in diabetes treatment even for people who had not taken action to change their lifestyles, i.e., people with lower stages of behavioral change at baseline. As expected, the results showed more pronounced improvement in glycemic management in these individuals. The fact that these individuals were likely to change their behavior, leading to therapeutic effects, was considered a clinically meaningful outcome. In this study, the TTM scores at 12 weeks were not used to assess whether behavioral changes had occurred. This is because the TTM scores after the intervention were considered to have been affected by study participation and therefore did not reflect the participants’ autonomous behavioral changes. Further investigation is required to determine whether use of TOMOCO™ in combination with Fitbit will promote to essential behavioral changes.
Although limited to speculation at this stage in our research, we also considered the following four reasons for the continued use of TOMOCO™ and Fitbit and for the participants’ continued motivation, with resultant improvement in their glycemic conditions. First, the Fitbit is a wristband-type activity tracker that enables its users to measure their activity level and check it even when they are not carrying a smartphone. In this study, by transferring the accurate step count data acquired by the Fitbit to the TOMOCO™ app, the participants received encouraging messages from the concierge on the TOMOCO™ app based on the data. These complementary roles of the TOMOCO™ app in combination with Fitbit may have motivated the participants to achieve their daily goals. Second, the TOMOCO™ app allowed the participants to easily record their meals with photographs and/or select meals from a list. This simplicity may have contributed to their continued use of the app. Third, the participants were able to enjoy self-management by performing activities within the app, such as games that provided rewards for continuing to achieve their daily goals and competing with other TOMOCO™ users according to the ranking of points earned. Fourth, these data were also integrated into the TOMOCO™ web system and used to provide consistent guidance by the HCPs during consultations. We consider this combination of the TOMOCO™ app and Fitbit device to have enabled HCPs to understand each participant’s lifestyle, including both physical activities and diet in more detail, and thus provide more precise advice. However, this remains speculative because each individual intervention was not evaluated. Considering the findings of this study, we infer that the TOMOCO™ app in combination with Fitbit complementarily led to behavioral changes in the participants and that this system provided useful information for guidance by HCPs, leading to improved glycemic management. Several other studies have supported the idea that complex systems involving activity tracking, automated feedback, gamification, self-evaluation, and in-person feedback by HCPs can improve people’s motivation and provide benefits [12, 15].
This study had three main limitations. First, it was a 12-week exploratory, single-arm study conducted in a single center. Second, the study population included participants who were not obese, had short disease duration, and had fewer micro- and macro-vascular complications. Third, this study excluded people who had difficulty using the lifestyle improvement support apps and wearable devices, as judged by the investigator. However, the effectiveness of lifestyle improvement support apps and wearable devices in the real world may be affected by individual smartphone usage and information technology literacy. Therefore, further investigations are required to allow generalization of the results. We would like to note that TOMOCO™ assists people with setting goals and encourages them, but it does not provide medical guidance. It is a supportive tool that encourages behavioral change in people with T2DM and enables HCPs to provide more specific guidance based on the data recorded in TOMOCO™.
Conclusions
The unique features of the TOMOCO™ in combination with Fitbit, together with conventional therapy, may promote a healthy lifestyle and thus contribute to improving HbA1c in people with T2DM.
Acknowledgements
We thank the participants and their families, the research institute staff, the study coordinators, and all others who were involved in this study. We would like to express our sincere gratitude to the ethics committee established by Saga Memorial Hospital for their invaluable guidance and support throughout the duration of this study.
Medical Writing, Editorial, and Other Assistance
We also acknowledge Takafumi Hashimoto (Mitsubishi Tanabe Pharma Corporation) for providing helpful advice regarding the study design and statistical analysis. Yusaku Watanabe and Kazumichi Minato (Tech Doctor Inc.) for providing consultation services and technical support for the Fitbit analysis, and Naoko Abe (Habitus Care Inc.) for providing consultation and technical support for the TOMOCO™ analysis. We acknowledge the support of ASCA Corporation in the editing of a draft of this manuscript. Funding for consultation, technical support, and editing support was provided by Mitsubishi Tanabe Pharma Corporation.
Declarations
Conflict of Interest
Makoto Kunisaki has received clinical commissioned study fees from Mitsubishi Tanabe Pharma Corporation and Novo Nordisk Pharma Ltd. Akiko Takahashi, Manabu Ishii, Yurika Kino, Kazuyo Sasaki, Takahiro Matsui, and Kenji Arakawa are employees of Mitsubishi Tanabe Pharma Corporation.
Ethical Approval
All procedures were conducted in accordance with the Declaration of Helsinki and the local regulations. All participants gave written informed consent. Site monitoring was conducted by EPS Corporation (Tokyo, Japan). Since the study site did not have its own ethical review body, this study was reviewed and approved by the certified ethical review committee established by Saga Memorial Hospital (ID. 16000061). The study was registered in the Japan Registry of Clinical Trials (jRCT ID: 1070220007).
Open Access This article is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License, which permits any non-commercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc/4.0/.
Effectiveness of a Lifestyle Improvement Support App in Combination with a Wearable Device in Japanese People with Type 2 Diabetes Mellitus: STEP-DM Study
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