DTEC: An opportunity to facilitate and extend REMIT support.

Patients who experienced the REMIT trial experienced positive results such as weight loss without feeling starved, maintaining sugar levels after the trial ended, or reduced medications. One patient shared, “At the conclusion of the REMIT trial, I mean I’d been drug free, you know for a year. That part was good and it was satisfying to be part of a study that actually showed benefit.” However, patients often wished they could continue to benefit from the intervention. Some noted they felt the intervention was unsuccessful because the results weren’t maintained after the trial. “Eventually… my blood sugar crept up again, and then I was back on metformin. During the REMIT protocol I was not on metformin.” Others did not hit the targets within the span of the trial but still felt there was value, like this patient who shared, “I think I left [REMIT] with definitely a better grasp and I keep my numbers at a more suitable level… I haven’t had an A1C over the 6.4… in… two years now.”

DTEC may provide a mechanism for extending REMIT support during and after trial completion in a scalable and spreadable way. One patient shared, “I wouldn’t say I have any certainly negative concerns about the transition out of [REMIT]… Except then it was over.” Health coaches and patients shared the challenge of transitioning from having high-touch interactions to no further support. Clients also felt alone, without support, and with a loss of accountability and motivation. They wished for a “mechanism where you can [give] more of a daily feedback [for] someone.” Health Coaches shared, “What I would hear is, ‘you know I talked to you almost every day and you were part of my life and then all of a sudden you were gone.’” And, “There has to be some way where when you’re no longer there that they can still continue as efficiently as they were and not feel like they’re alone.”

Participants described the opportunity of DTEC to support programmatic components of the REMIT intervention to include messaging and self-management education. A health coach suggested messaging to send and respond to quick one liners, “You can just say, ‘hey, you know what I was wondering about this is, is this something I can even think about or I just heard this on the radio is that relevant?’” This is corroborated by Nelson et al who have provided evidence supporting the use of text messaging both to address scale and reduced health literacy disparities [33]. However, our participants suggest taking this further. Participants desired functionality for supporting carb counting and tailored learning opportunities. For example, a health coach noted, “There’s so much information [available on the internet and other sources] that they don’t know how to relate it to themselves and personalize it”. Specific examples of tailoring education included passive methods like curating links to reliable information sources (health coach suggestion), to interactive self-management support to motivate and engage patients through actionable next-steps.

“Like if you had a glucose reading after like 2 hours after breakfast and [the app says], ‘Oh your glucose reading is a little bit on the higher end. These are the things that you can do next at your next meal to kind of make it lower.’… so a little bit more interactive to… self-guide the user.”–Patient

Acceptability: DTEC is convenient, efficient and scalable.

Acceptability was defined as participants’ perceptions of the palatability for DTEC and may affect the scalability and spreadability of DTEC. Health coaches noted in-person meetings were beneficial, especially for reading body language to help them meet clients where they are at. However, several mentioned that in-person can be inaccessible or infeasible, as previously done in the REMIT trials. A health coach shared, “Asking someone to come in for a 15-minute appointment regularly is a lot for the patient in terms of paying for parking and taking time away from their day and commuting to the hospital.” A patient highlighted, “[The DTEC prototype] seems to be maybe a quicker method and it’s right at your fingertips.” This general perceived value is further expanded upon through the perceived acceptability, adoption, feasibility and appropriateness of DTEC by health coaches and patients.

Participants noted DTEC would not only support convenience but suspected it would also improve efficiency and be more cost-effective for scaling REMIT. A health coach shared, “It would allow you not to have to skip appointments or do it over the phone rather than do it in person. It also gives you more flexibility [regarding access in remote regions]”. Another noted, “We need to figure out how do we take this approach that we’ve been working on and researching for all these years and roll it out to the population in a way that is cost efficient.”

Patients shared enthusiasm for the concept and perceived it to support diabetes management as a means to scale and spread the REMIT intervention. One patient stated, “I think it’s a great idea, I really like the idea of this app. I think it’s going to help a lot of people.” Another patient shared,

“Well, I mean the use of smartphones is the way of the world now, right? So I think it’s very consistent with our use of technology. Diabetes is a complex topic with a bunch of interacting factors, so something that kind of gathers information guides, reports back, connects you with [other individuals]… It’s a great way to go, actually.”–Patient

Adoption: DTEC may motivate through connecting behaviours to outcomes.

Adoption was defined as participants’ perceptions of how other patients or health coaches would use it. Participants highlighted how DTEC would support ease of sharing data with their health care team, and simplify tracking which would support its scale and spread. A patient shared, “I feel like if it’s all in one place it’s easier, it’s less overwhelming, and again, just quicker.” A health coach noted, “I would love to try it…We can look at the blood sugar, visuals in the middle of the conversation, which we don’t do on a regular basis because it’s not as practical.”

Participants identified that DTEC may help motivate or build intuitive connections between behaviours and their impact on measurements. This value added may positively impact DTEC’s spreadability through potential higher uptake of technology. Health coaches stated, “It’s practical for a regular clinic appointment that they could bring those numbers to their physician or diabetes nurse in the future outside of the study period. And because it tracks overtime, it may be motivating for the patient.” and “seeing visuals of things…It’s motivating ‘Hey, I’m almost there. I’ve done something.’ you know, give some feeling. That they’re on their way and to achieving their goals.” A patient imagined they were looking at their digital health application which showed their blood sugars for the last two weeks and said, “‘very well hold on, this is what I had the last two weeks. Oh my God, my blood sugars were up in like the fifteens I gotta stay away from that. Let’s try something else.’ I think that would be a very positive way of keeping people on the right track.” Another patient noted, “I kind of like the activity or the minutes or the steps or something like that. Because then it’s sort of like, oh, I only have 1200 steps. I better go for a walk.”

Feasibility: Opportunity for lower-effort demands for sustained use.

Feasibility was defined as participants’ self-perception of their own or others’ ability to use a virtualized version of the REMIT intervention given available time, resources, workflow, and skill considerations. Participants identified the opportunity for added flexibility to improve feasibility and sustained use. They noted that while intensive data collection on a digital health platform would be supportive during the intensive period of the REMIT intervention, especially as the level of manual data entry of every meal, activity and blood glucose reading may be burdensome without automation for sustained use.

One patient shared, “I would like that ability to take a note that said…You know, I was at a party and throughout the evening [this] is what I ate.” A health coach reinforced this also, “From my perspective, not being a dietitian, I don’t think [tracking every pre and post meal with food photography] would be helpful for me and I think it might be burdensome for the patient.” However, within the research context, the value and feasibility may be higher and more supportive for a digital health platform to facilitate data entry. This may indicate the ability to scale and spread DTEC could depend upon which sphere of application is implemented.

"So it would definitely improve, I think, just participants’ ability to record data in a timely fashion. I would say there are a good number [of research participants] who are, you know, filling out [diaries] in the 5 to 10 minutes before they show up for their appointment.”—Health Coach

However, equitable access warrants additional consideration for the feasibility of scaling and spreading DTEC. A health coach noted, “the patient population that did REMIT… they would all have smartphones, but my regular patient population, not necessarily if they were older.” A patient highlighted that, “You have to have money to be diabetic [which includes having] a smartphone that’s up to date.” A health coach noted “we don’t see a lot of low income participants, I think, largely just because they don’t have the flexibility to participate in those kind of protocols.” This has implications for the format through which DTEC could be expanded; a health coach commented, “There’s a lot of low income patients that don’t have cell phones and so they have to make sure that it’s all provided to the patients.”

Appropriateness: Opportunity to provide compassionate insights and automate data entry.

Appropriateness was defined as the perceived fit-for-purpose as well as the degree to which the user can use the digital health tool for their disease management which may influence the ability to scale or spread the tool. The two main take-aways were (1) it matters what is being tracked, and (2) how information is communicated can greatly affect the use of DTEC, including possibly having it fail because of how it may interact to support or erode mental well-being.

Regarding what is tracked, participants felt functionality of a digital health platform would be supportive for self-management and health coaching during the remission protocol. Specifically on the ability to communicate through DTEC, one health coach shared, “I definitely think that with health coaching, it’s a very valuable tool to be able to communicate with the patient…through the phone calls or videos or emails. And I think it really helps with motivation for people.”

Regarding how information is communicated, several participants commented on the value of visualizing trends. For example, a health coach shared, “It’s a quick glance and it gives you the information you need to target.” Participants commented on how DTEC could support gaining deeper insights. A health coach shared, “It’s really helpful to see [trends]… we kind of can see before breakfast, they don’t have any issues with their blood sugars. But maybe before dinner is more problematic.” However, participants also flagged that while self-management data, including meal intake, blood glucose medication, exercise and goals are helpful, care should be taken in how results are presented. For example, one patient noted, “I feel like weight is a good thing to have in there, but I feel like it should be a little bit to the background because if it’s too much to the forefront, I think it’s too like ohh I failed.” In line with this, patients identified the need for consideration around impacts of data presentation on mental well-being. For example, an overemphasis on BMI or weight may result in feeling like a failure or prohibiting use. One patient said, “I just hate to think that maybe anybody who’s using this app for the first time will keep seeing BMI and it [might] turn them off… might make them go to extremes, yeah?”. Another patient commented, “I do think there should be some set goals like I don’t want to exclude goals but I just feel like you have to be cautious about it.”

Sampling.

We engaged participants throughout the co-design process to ensure end-users’ needs and experiences guided the technical solution. Specifically, our sample of participants included patients living with T2D, and health coaches with previous experience with any REMIT study. More specifically, eligibility included (1) patients living with diagnosed T2D, or health coaches providing care for individuals with T2D, (2) having participated in a REMIT trial, (3) over the age of 18 years, and (4) understand English sufficiently to consent and complete study activities. We estimated a sample of three to six patients and three to six health coaches to reach thematic saturation.

Data collection.

In alignment with qualitative principles of theoretical data saturation, our team iteratively assessed and reassessed the need for additional interviews throughout the data collection period to ensure conceptual depth was achieved [52]. Recruitment targets were met with a purposeful sample of 6 patients and 6 health coaches and conceptual depth was achieved with good overlap across participant feedback. Due to the COVID-19 pandemic, data collection was collected virtually through a secure video conferencing platform (Microsoft Teams). After obtaining informed written consent (REDCap) [45,46], all participants completed a testing session of 60–90 minutes inclusively consisting of a pre-study questionnaire (patients only), semi-structured interviews, and a cognitive walkthrough [50]. The patient-only pre-study questionnaire probed demographics, experience with diabetes management, and technology use. Semi-structured interviews were conducted with research staff. Interview guides (S1 Appendix) were designed to probe: (1) experiences with T2D management before and during the REMIT study, (2) participants’ level of comfort with using technology, and (3) participants’ level of comfort with integrating technology into the REMIT intervention. All participants completed a cognitive walkthrough to garner feedback on an early prototype to support the digitally-enabled version of REMIT. Each group (patients and health coaches) was presented with various scenarios, specific to their role, and shown DTEC prototypes from associated screens from the digital tool, bant (via the screen share option on Microsoft Teams).

Data analysis.

Participant demographic data was analyzed via descriptive statistics. To contextualize our data, while ensuring high-quality qualitative analysis, we outlined our team’s positionality to describe how each of the researchers’ identities, values, experiences, and social positionings may have influenced data collection, analysis and interpretation [53] (S2 Appendix).

Transcription of interviews and cognitive walkthroughs were conducted by UHN research team members. Transcripts were analyzed in two phases. First, DN and MT developed a codebook based on emerging themes informed from thematic content analysis of the interview data using Nvivo software (Version 12). During codebook development, authors DN, MT reviewed four transcripts which was independently applied to two additional transcripts by DN and MT. Each coder independently coded assigned transcripts. From there, the codebook was iteratively refined to remove ambiguity and overlap while providing flexibility for adding emerging themes. The finalized codebook was used for formal analysis. The second phase of analysis, completed by MT, DN, and KJP, involved mapping themes onto concepts of acceptability, adoption, feasibility, which were loosely informed by the Implementation Outcome Framework (IOF) [44]. Finally, these IOF concepts were linked based on how they relate to the scale and spread of the REMIT intervention.