The Science of Diabetes Self-Management and Care2024, Vol. 50(6) 497–509© The Author(s) 2024Article reuse guidelines:sagepub.com/journals-permissionsDOI: 10.1177/26350106241285829journals.sagepub.com/home/tde
Abstract
Purpose: The purpose of the study was to describe the development and feasibility of implementing the DM-BOOST program in support of an established diabetes self-management education and support (DSMES) program.
Methods: A patient panel of 4 adults with type 2 diabetes (T2DM) codesigned DM-BOOST. DM-BOOST is a patient-focused program that includes peer-written text messages about diabetes self-management behaviors and digital health training to improve patient portal use and initiate goal setting prior to a scheduled DSMES appointment. Adults with T2DM and A1C ≥8.0% participated in a 6-month feasibility pilot. Participants were randomly assigned (1:1) to receive either DM-BOOST or usual care. Outcomes included DSMES engagement (scheduled and attended DSMES appointments) and changes in diabetes self-efficacy and treatment satisfaction.
Results: Pilot participants (n = 60) were 60.0% female with mean age 45.5 years (SD 8.3) and A1C 10.1% (SD 1.8%). All DM-BOOST participants (30/30, 100%) had DSMES appointments scheduled compared to 86.7% of usual care (26/30). DM-BOOST participants had fewer DSMES appointment no-shows/cancellations (3/30, 10%) compared to usual care (10/26, 35%). There was greater improvement in diabetes self-efficacy in the DM-BOOST group compared to usual care and no difference in treatment satisfaction.
Conclusions: DM-BOOST, leveraging peer-written text messaging and digital health training, increased DSMES engagement. Implementation of DM-BOOST was determined to be feasible, with several system-level barriers identified, including obtaining provider referrals and scheduling appointments. An effectiveness trial of DM-BOOST is needed to evaluate the impact on clinical outcomes.
Patient engagement with diabetes self-management education and support (DSMES) interventions lead to improvements in blood glucose control,1-7 diabetes knowledge,1,2,6,8 self-management skills,2,6 and self-efficacy.2,9 DSMES is efficient,10 reduces hospitalizations,11,12 and lowers overall costs of care.13 The American Diabetes Association’s Standards of Medical Care in Diabetes specifies that all people with diabetes should complete DSMES, especially at critical times such as at diagnosis, when not meeting treatment goals, when complicating factors develop (medical, physical, and psychosocial), and when transitions in life and care occur.14 Very few people with type 2 diabetes (T2DM), as low as 5% of Medicare beneficiaries and 7% of adults with private insurance, complete DSMES after being diagnosed.15-18 Analyses of national data estimate that only half of all adults with diabetes in the United States receive any DSMES.19 Low patient engagement with DSMES is especially seen among people who are medically underserved.20,21 Noncompleters of DSMES are more likely to have less education, lower social functioning, and poorer general and mental health.22 Low patient engagement with DSMES significantly reduces the impact of this recommended guideline of diabetes care.23
Numerous barriers to patient engagement in DSMES have been identified, including access and logistical (eg, transportation) challenges, medical or financial restrictions, low perceived benefit, competing priorities, and/or contrasting personal beliefs.18,24 Digital health tools offer the potential to address several of these patient access barriers.25,26 As such, consideration of using digital health tools to address barriers to access and improve satisfaction of DSMES has been included in the 2024 revisions to the Standards of Care in Diabetes.27 With mobile device ownership growing globally,28 telecommunication-based diabetes care has become increasingly utilized and accepted.26,29-33 Patient use of digital health tools to self-manage diabetes is rapidly increasing,34 demonstrating improvements in A1C35 and self-management behaviors, such as medication adherence.36,37 Digital health tools hold particular promise in facilitating behavior change, especially when developed through user-centered design approaches informed by behavioral theories.38 Involving patients directly in the codesign of these interventions may be a critical determinant of their success promoting the intended health outcomes.39
The DM-BOOST program was codesigned with patients with T2DM to improve DSMES engagement using digital health tools. Rooted in self-determination theory,40 DM-BOOST was designed to increase DSMES engagement by improving patient autonomy through personalized diabetes behavior goal setting, self-management competence through digital health training, and connectedness through peer-written text messages. DM-BOOST also incorporates principles of behavioral economics (BE). BE posits that humans behave in predictable patterns due to extrinsic contextual factors, providing opportunities to influence human behaviors in a desired fashion.41 In BE, a “nudge” is a strategy to influence decision-making.42 DM-BOOST attempts to nudge people toward improved diabetes self-management behaviors through the social influence of peer-written text message tips (eg, “PEER TIP: Being physically active does not mean you need to do a crazy workout. Even a few minutes of walking can help lower your blood sugar.”). Peer tips are followed by a nudge to initiate personal diabetes behavior goal setting (eg, “Tell us an exercise that is easy and enjoyable for you to do.”). DM-BOOST then leverages commitment bias, the BE concept that states people tend to remain committed to publicly exhibited behaviors. Patients verbally commit to the DM-BOOST research team that they will send their provider a patient portal message with their goal prior to their upcoming DSMES appointment.
The purpose of the study was to describe the development and feasibility of implementing the DM-BOOST program in support of an established DSMES program. The feasibility of conducting a research study within usual care practices to avoid negative consequences and the feasibility of the intervention producing a positive impact on patient behaviors were assessed. To assess feasibility of patient behavior change, whether patients receiving DM-BOOST had greater DSMES engagement (ie, attendance at initial DSMES appointments) compared with usual care, we examined secondary outcomes of interest, including changes in patient-reported diabetes self-efficacy and treatment satisfaction between treatment groups.
DM-BOOST was codesigned with input from a panel of patients using a generative codesign framework for health care innovation.43 Patient panel members joined a group meeting, called a Community Engagement (CE) studio,44 to provide insights of their experiences with DSMES, including barriers and facilitators to engaging with DSMES. Patient panel members also met individually with the research team to cocreate DM-BOOST program materials. Program materials included recruitment mailings, text messages, and the digital health training protocol. The patient panel then completed a usability assessment of DM-BOOST using the Think Aloud protocol.43 After DM-BOOST was refined, a 6-month randomized pilot was conducted comparing DM-BOOST with usual care. The study was approved by the Institutional Review Board (IRB) at the UMass Chan Medical School (IRB No. H00017902) and registered at clinicaltrials.gov (NCT04710940).
This study was conducted in collaboration with the UMass Memorial Health (UMMH) Diabetes Center of Excellence (Diabetes Center) in Worcester, MA. Their DSMES program is provided by certified diabetes care and education specialists (CDCESs) and is accredited by the Association of Diabetes Care and Education Specialists (ADCES). Patient panel members had T2DM and has previously completed DSMES (n = 4). Participants in the randomized trial (n = 60) had the following inclusion criteria: (1) a T2DM diagnosis, (2) most recent A1C ≥ 8.0% within previous 12 months, (3) received primary care at UMMH, and (4) English language fluency. Exclusion criteria included self-report of previously completing DSMES.
To recruit patient panel members, people with T2DM who had previously completed DSMES were identified from the UMMH electronic health record (Epic EHR). Identified patients were mailed an information letter and a stamped opt-out postcard. Patients who did not return the opt-out postcard after 2 weeks from mailing date received 1 telephone call to assess their interest in joining the patient panel. Interested patients provided informed consent prior to completing the intervention codesign activities and usability testing. Intervention codesign activities consisted of participating in 1 CE studio, 2 individual sessions with the research team to codesign intervention components, and 1 usability assessment.
The CE studio format is a structured approach to obtain input from key people to inform research.44 The DM-BOOST CE studio was a 2-hour meeting conducted virtually over Zoom in December 2020 due to the COVID-19 pandemic. It was facilitated by an experienced, neutral moderator who met with the research team prior to developing a CE studio guide. Attendees included the moderator, the patient panel, the study’s principal investigator (DJA), and two research team members (LS and SW). The CE studio started with a brief presentation by DJA, followed by a guided group discussion to collect input on the patient panel’s experiences with DSMES, the barriers they experienced engaging with diabetes self-management training, and facilitators they either experienced or believed would be helpful for future diabetes self-management training engagement. At the conclusion of the CE studio, the moderator provided the research team with a written summary of meeting notes and a list of key recommendations. The key recommendations were to (1) inform patients that insurance covers the cost of the training; (2) emphasize the benefits of DSMES and that it has been proven to help; (3) deploy multicontact approach for initial engagement, including phone calls, texting, patient portal messaging, and/or emailing; (4) include testimonials or tips from peer patients via text messages; (5) send initial information about DSMES from their diabetes care providers; (6) highlight the technological components of the program so people know it is “cutting-edge”; (7) provide clear instructions on how to access in-person and/or virtual appointments; and (8) inform patients that the program is personalized to help them reach their diabetes goals.
Individual codesign sessions were then conducted virtually over Zoom from February to June 2021 to develop DM-BOOST. Patient panel members reviewed drafts of recruitment materials and provided feedback. They were then asked to think of a recommendation they would provide a friend or family member for each of 7 ADCES diabetes self-management behaviors. They were also asked to provide tips for using the Epic MyChart patient portal, describe the patient portal functions they believed were most important to train patients on, and give recommendations on training approach. The codesign sessions were recorded and transcribed by the research team to generate peer tips and goal-setting text messages and to develop the digital health training protocol.
Patient panel members then completed a usability test of all DM-BOOST program components and provided user experience feedback via a semi-structured interview for program refinement. Patient panel members suggested edits to the text messages and ranked the messages from most to least favorite. This ranking informed the order in which the text messages were to be sent out in the feasibility pilot, with the most liked messages for each diabetes self-care behavior received first.
A list of potentially eligible patients was generated from the EHR based on the following criteria: age >18 years old, diagnosis of T2DM (ICD-10 code: E11.9), most recent A1C lab ≥8.0% within past 12 months, and no DSMES completed (CPT codes G0108 or G0109). Potentially eligible patients were mailed an invitation letter and a stamped “Active Choice” postcard. The postcard highlighted peer-informed benefits of completing DSMES and listed multiple options for patients to state their communication preference. Patients who did not return the postcard after 2 weeks received a telephone call to assess their interest in scheduling a DSMES appointment and participating in the study. All patients who were interested in completing DSMES received assistance scheduling the appointment. The research team sent an EHR “In Basket” message to each patient’s primary care provider (PCP) to inform them that their patient would like to complete DSMES and request that the PCP submit an EHR referral for DSMES to the UMMH Diabetes Center. Patients were also offered help with scheduling the DSMES appointment once the referral had been placed. Patients interested in participating in the accompanying study provided informed consent and were randomly assigned (1:1) to either the DM-BOOST program or usual care. The randomization table with blocks of 4 was created by a study biostatistician (JL) and programmed into the study’s data collection system (REDCap) so that participants were randomly assigned after completion of the baseline questionnaire.
Among the 460 patients screened and mailed Active Choice postcard invitations between November 2021 and March 2022, 20 (4.3%) mailed back the postcard. Of these 20 patients, 17 responded that they were interested in receiving DSMES, and 3 opted out from receiving further contact. The remaining 440 patients received a single recruitment phone call to assess their interest. Fifty-two percent of all screened patients were reached through the single recruitment phone call attempt. Among those reached, 32% were interested in either receiving DSMES alone (5%) or DSMES and study participation (27%). The recruitment rate for the pilot was 13.0% (60 enrolled/460 invitations mailed).
The DM-BOOST program consisted of a text messaging program and a digital health training appointment. Text messaging began immediately after enrollment with personalized welcome messages. Participants then received 2 messages per week with diabetes self-management behavior tips written by peer patients, followed by a nudge to reply with their own personal goals for a diabetes self-management behavior. Participants were also informed that the research team will review text message replies at the digital health training appointment and were provided with a phone number to call for assistance. Peer text messages were sent until the date of the participant’s digital health training appointment.
Prior to the digital health training appointment, research team members assisted participants with patient portal enrollment and authentication as needed. The research team also verified that each participant knew how to access the portal. The digital health training protocol reviewed 4 key patient portal functions: (1) visits: scheduling future appointments, connecting for a telehealth appointment, and accessing previous appointments; (2) medications: accessing current medications and requesting prescription refills; (3) test results: accessing test results and comments from care team; and (4) communication: sending and receiving messages and letters from the care team. The training included steps on how to join a telehealth appointment and allowed for patient questions regarding the patient portal.
The research team reviewed text message replies with participants individually to set a diabetes behavior goal. If the participant did not reply to any goal-setting nudges, they were asked to choose one of the 7 diabetes selfmanagement behaviors that was most important to them. With assistance, each participant created a SMART (specific, measurable, attainable, relevant, and time-based) diabetes self-management goal, which was sent to each participant by the research team via a patient portal message. Participants were then asked to commit to the DM-BOOST research team that they would retrieve the patient portal message and send their SMART goal via a patient portal message to the CDCES they were scheduled to meet with for DSMES.
For the usual care comparison group, participants received routine health care from their providers at UMMH, including access to and support scheduling a DSMES appointment. Usual care group participants did not receive any text messages or digital health training.
All participants completed a baseline questionnaire upon enrollment. The baseline questionnaire contained items on sociodemographic variables and patient-reported outcomes. Participants were sent a follow-up questionnaire 3 months after enrolling in the study. A final semi-structured interview was conducted, guided by the unified theory of acceptance and use of technology,45 and audio recorded and transcribed verbatim. Participants received a $25 gift card upon completion of each questionnaire and interview. EHR data containing DSMES activities completed, cancelled, or no-showed were collected 6 months after each participant’s study enrollment date. Research team members conducting the medical record review were blinded to treatment group allocation.
The primary outcome was engagement with initial DSMES appointment after enrollment, based on the completion status in the EHR. DSMES appointments were available both in person and via telehealth, based on patient preference. For DSMES appointments that were rescheduled, the next appointment scheduled was considered the initial DSMES appointment. For all participants who completed an initial DSMES appointment, it was determined whether a follow-up appointment was scheduled and completed within 6 months after enrollment.
Additional secondary outcomes included changes in patient-reported diabetes self-efficacy and diabetes treatment satisfaction over 3 months. The Diabetes Empowerment Scale short form (DES-SF) was used to measure overall diabetes-related psychosocial self-efficacy. The DES-SF includes 8 Likert-type items asking patients to report on how much they agree about statements related to their personal diabetes self-management. The scoring of the DES-SF is based on the total of items. Checked items are scored as follows: strongly agree = 5 points, agree = 4 points, neutral = 3 points, disagree = 2 points, and strongly disagree = 1 point. The total DES-SF score is calculated by averaging the sum of all the items. The higher the DES-SF score is, the greater the patient’s selfefficacy. The DES-SF scale has established reliability and validity.46 Diabetes Treatment Satisfaction Questionnaire (DTSQ) and DTSQ Change (DTSQ-c) scales were used to measure satisfaction with diabetes treatment (and change in measure given ceiling effects) in people with diabetes.47,48 The scoring of the DTSQ is accomplished by summing 6 of the 8 items, with responses ranging from 0 = very dissatisfied to 6 = very satisfied. Two DTSQ items focused on perceived frequency of hyperglycemia and hypoglycemia are assessed separately with responses ranging from 0 = none of the time to 6 = most of the time. The scoring of DTSQ-c includes the same items as the DTSQ, with scores from −3 = much less satisfied now to 3 = much more satisfied now for the 6 treatment satisfaction questions that are summed to generate a DSTQc score. The 2 items focused on perceived frequency of hyperglycemia and hypoglycemia are scored from −3 = much less of the time to +3 = much more of the time. Negative scores for these 2 items thus represent fewer problems with blood glucose levels.
Because the objective of this study was to assess feasibility, the pilot was not powered to assess efficacy. The target sample size (n = 60) was determined based on best practices for design and analysis of pilot studies (at least 30 participants per trial arm).49 Differences in initial DSMES engagement and follow-up appointment between groups were assessed using chi-square test. Two-sample t tests were used to compare changes in diabetes self-efficacy and treatment satisfaction mean scores. International guidelines for analysis and reporting of clinical trial intention-totreat principles were followed.50 Data were analyzed in R Statistical Software (version 3.6.1).51
Study participants (n = 60) had mean A1C of 10.1% (SD 1.8%) and age 45.5 (SD 8.3) years. The study population was 60% female. The majority of participants were White (65.0%), followed by more than 1 race (15.0%), African American (8.3%), and Asian (5.0%). Four participants (6.7%) preferred not to answer, and 33.3% of the study population identified as being Hispanic/Latino ethnicity. A wide spread of education and income was observed (Table 1).
All of the participants randomly assigned to the DM-BOOST group scheduled a DSMES appointment (30/30) compared to 86.7% (26/30) of those receiving usual care (P = .04). Reasons for DSMES appointments not being scheduled included not receiving a referral from PCP (n = 2), concerns about paying for copays (n = 1), and changing their minds about wanting to complete DSMES (n = 1). Retention for the 3-month follow-up questionnaire was 78.3%. Among those completing the follow-up questionnaire, 76.6% (36/47) completed the follow-up interview (DM-BOOST: n = 19; usual care: n = 17; see Figure 1).
In the DM-BOOST group, 25 of 30 (83%) participants received the peer tips text messages. Five participants scheduled a DSMES appointment for the same week as study enrollment. This did not allow enough time for the text messages to begin on the following Monday. Among those who received at least 1 peer tip and nudge text message, 60% (15/25) responded to at least 1 of the goal-setting messages with a personalized diabetes self-management behavior.
Next, 87% (26/30) completed the digital health training. The 4 participants who did not complete training had scheduled their DSMES appointment immediately after enrolling in the study. Among participants who completed the training, 80% (21/26) successfully sent a patient portal message with their personal SMART goal to their CDCES. The goals were focused on healthy eating (76%), improved monitoring (28%), being active (24%), taking medication (24%), healthy coping (8%), and reducing risks (4%).
For DM-BOOST, 27 of 30 (90%) participants completed an initial DSMES appointment compared with 16 of 30 (53.3%) participants receiving usual care (P = .001). The no-show/cancellation rate for DM-BOOST was 10.0% (3/30) compared to 38.5% (10/26) for usual care (P = .01). Among the 43 participants that completed an initial DSMES appointment, 76.7% scheduled a follow-up DSMES appointment (DM-BOOST: 22/27; usual care: 11/16). The no-show/cancellation rate for the follow-up DSMES appointment was 59.1% for DM-BOOST participants (13/22) compared to 36.4% for usual care (4/11; P = .14). Rates for completing at least 1 follow-up DSMES appointment within the 6 months of study participation were similar: 26.7% (8/30) in DM-BOOST and 23.3% (7/30) in usual care (P = .77). See Table 2 for results on participant engagement with DSMES.
Table 3 shows results from the diabetes self-efficacy scale, and Table 4 shows results from the DTSQ and DTSQ-c. Improvements in diabetes self-efficacy were seen in both groups with mean change for DM-BOOST at 0.8 (SD 1.2) compared to 0.2 (SD 1.1) for usual care (P = .05 difference between groups). Both groups reported high diabetes treatment satisfaction at baseline. Improvement in diabetes treatment satisfaction were similar between groups: mean DTSQc score of 10.2 (SD 7.6) for DM-BOOST compared to 13.1 (SD 5.5) in usual care (P = .07).
A patient codesign approach was deployed to develop DM-BOOST, a digital health-based program to increase patient engagement with DSMES. A randomized pilot study was then conducted to assess feasibility of implementing DM-BOOST. In the feasibility assessment, the study was able to successfully recruit, enroll, randomize, and collect data from the target number of participants. Potential implementation barriers identified during feasibility pilot included unexpected challenges obtaining provider referrals and coordinating patient scheduling of DSMES appointments. Some participants in the DM-BOOST group did not receive the full intervention, mostly due to the initial DSMES appointment being scheduled before the intervention components could be delivered. Participants receiving DM-BOOST showed greater completion and lower no-show/cancellation rates for initial DSMES appointments compared to those receiving usual care. However, this improvement in engagement was not sustained through follow-up DSMES appointments. This is not surprising given that the DM-BOOST program was designed to be delivered only during the waiting time period after scheduling and prior to attending the initial DSMES appointment. Because the purpose of this study was to assess feasibility, further investigation with a larger sample and extended contact is required to determine program efficacy. The identified implementation challenges and lessons learned during the feasibility pilot will be important to consider in future trials.
Because the DM-BOOST program involved the use of multiple digital health tools (ie, text messaging, patient portals, and telehealth appointments) and behavior change strategies (ie, increasing relatedness, autonomy, and competence), it is difficult to isolate the potential impact of each DM-BOOST component. Frequent contact with patients (eg, through text messages) prior to scheduled appointments may be an essential strategy to increase DSMES attendance. This is consistent with other studies that have shown improvement in appointment adherence through simple text message reminders across a variety of specialties.52 Research has also shown that peerwritten or self-written messages may be preferred over “expert” written messages.53,54 Because DM-BOOST sends text message tips and nudges that are written by peers, this may also increase relatedness and better normalize DSMES for individuals, addressing a critical need for increasing motivation to perform a desired behavior.
DM-BOOST may also be effective through digital health training that focused on improving the use of the patient portal. Studies examining patient portal use among people with T2DM demonstrate a growing interest among patients by facilitating communication and access to care and promoting behavior change; although, there has been a mixed impact on glycemia over time.55,56 A web-based survey in Canada showed a lower no-show rate related to patient portal use with missed appointments recorded in 9.5% of non-patient portal users compared to 4.5% of patient portal users.57 However, patient portal use, despite promotion by health care systems, remains remarkably low, with only 29.3% of a nationally representative sample of US adults reporting accessing their portal in 2017 to 2018.58 Individuals without a regular doctor or health insurance, with less than college education, and with limited English proficiency are all less likely to use patient portals.58 Improving patient competence with portals to improve diabetes self-management engagement and communication with providers may address inequities and be an impactful and scalable component of the DM-BOOST program.
DM-BOOST also promoted personalized diabetes self-management behavior goal setting and communication with CDCES personnel prior to DSMES appointments through the digital health training. This may increase patient perception of autonomy and accelerate behavior change attempts with the CDCES. Also, patients may feel committed to attending their scheduled training (commitment bias) after their intention of behavior goals and appointment attendance were stated when they sent their personal goal to the CDCES in advance. This integration of promoting self-management behavior change activities and outcomes involving the patient portal remains largely untested among people with T2DM. Alongside the DM-BOOST peer text message nudges, the behavior change strategies used during the digital health training may be more sustainable than existing BE interventions to improve diabetes self-management, which have largely focused only on the use of financial incentives.59
There are a number of study limitations to note. First, the study was not powered to detect clinically meaningful differences. Missingness of A1C data in the EHR limited the ability to estimate the program’s preliminary effects on glucose control. The study took place in a specialty diabetes clinic at a single academic medical center, limiting generalizability of implementation feasibility in patient populations with limited access to specialty diabetes care. Given the common need to improve DSMES at community health centers and more diverse primary care environments, future studies should engage these practices. The study also only recruited 13% of the patients screened for eligibility, further limiting generalizability of the findings.
In conclusion, it was determined that implementing DM-BOOST alongside an established DSMES program via a randomized pilot study was feasible. Positive results from the pilot found that DM-BOOST leads to increased patient engagement with initial DSMES appointments. Despite improvement in the initiation of DSMES observed, improved engagement with DSMES was not sustained at follow-up appointments. This is also commonly seen in other DSMES programs and remains a substantial challenge.60,61 Ongoing work is focused on qualitative analyses of the follow-up interviews and increasing the reach of the program through translation and cultural adaptation for people with limited English proficiency. The DM-BOOST program is currently being culturally adapted for Spanish speaking Latinx patients (NIDDK K01DK131318), and additional strategies to sustain engagement in DSMES are being considered for future work.
This work was funded in part by the National Institutes of Health National Center for Advancing Translational Sciences (KL2TR001455) and National Institute of Diabetes and Digestive and Kidney Diseases (K01DK131318).
Daniel J. Amante https://orcid.org/0000-0003-1488-9624
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From Department of Population and Quantitative Health Sciences, UMass Chan Medical School, Worcester, Massachusetts (Dr Amante, Ms Shenette, Ms Wainaina, Ms Balakrishnan, Ms Bhatia, Dr Lee, Dr Lemon, Dr Gerber); Department of Medicine, UMass Chan Medical School, Worcester, Massachusetts (Dr McManus, Dr Harlan, Dr Malkani); and Diabetes Center of Excellence, UMass Chan Medical School, Worcester, Massachusetts (Dr Harlan, Dr Malkani).
Corresponding Author:Daniel J. Amante, Population and Quantitative Health Sciences, UMass Chan Medical School, 55 Lake Ave North, Worcester, MA 01655, USA.Email: daniel.amante@umassmed.edu
