Effectiveness of an Immersive Telemedicine Platform for Delivering Diabetes Medical Group Visits for African American, Black and Hispanic, or Latina Women With Uncontrolled Diabetes: The Women in Control 2.0 Noninferiority Randomized Clinical Trial.

BACKGROUND: Medically underserved people with type 2 diabetes mellitus face limited access to group-based diabetes care, placing them at risk for poor disease control and complications. Immersive technology and telemedicine solutions could bridge this gap. OBJECTIVE: The purpose of this study was to compare the effectiveness of diabetes medical group visits (DMGVs) delivered in an immersive telemedicine platform versus an in-person (IP) setting and establish the noninferiority of the technology-enabled approach for changes in hemoglobin A1c (HbA1c) and physical activity (measured in metabolic equivalent of task [MET]) at 6 months. METHODS: This study is a noninferiority randomized controlled trial conducted from February 2017 to December 2019 at an urban safety net health system and community health center. We enrolled adult women (aged ≥18 years) who self-reported African American or Black race or Hispanic or Latina ethnicity and had type 2 diabetes mellitus and HbA1c ≥8%. Participants attended 8 weekly DMGVs, which included diabetes self-management education, peer support, and clinician counseling using a culturally adapted curriculum in English or Spanish. In-person participants convened in clinical settings, while virtual world (VW) participants met remotely via an avatar-driven, 3D VW linked to video teleconferencing. Follow-up occurred 6 months post enrollment. Primary outcomes were mean changes in HbA1c and physical activity at 6 months, with noninferiority margins of 0.7% and 12 MET-hours, respectively. Secondary outcomes included changes in diabetes distress and depressive symptoms. RESULTS: Of 309 female participants (mean age 55, SD 10.6 years; n=195, 63% African American or Black; n=105, 34% Hispanic or Latina; n=151 IP; and n=158 in VW), 207 (67%) met per-protocol criteria. In the intention-to-treat analysis, we confirmed noninferiority for primary outcomes. We found similar improvements in mean HbA1c by group at 6 months (IP: -0.8%, SD 1.9%; VW: -0.5%, SD 1.8%; mean difference 0.3, 97.5% CI -∞ to 0.3; P<.001). However, there were no detectable improvements in physical activity (IP: -6.5, SD 43.6; VW: -9.6, SD 44.8 MET-hours; mean difference -3.1, 97.5% CI -6.9 to ∞; P=.02). The proportion of participants with significant diabetes distress and depressive symptoms at 6 months decreased in both groups. CONCLUSIONS: In this noninferiority randomized controlled trial, immersive telemedicine was a noninferior platform for delivering diabetes care, eliciting comparable glycemic control improvement, and enhancing patient engagement, compared to IP DMGVs. TRIAL REGISTRATION: ClinicalTrials.gov NCT02726425; https://clinicaltrials.gov/ct2/show/NCT02726425.

The Physical Activity Assessment of Adults With Type 2 Diabetes Using Accelerometer-Based Cut Points: Scoping Review.

BACKGROUND: Incorporating physical activity into lifestyle routines is recommended for individuals with type 2 diabetes. Accelerometers offer a promising method for objectively measuring physical activity and for assessing interventions. However, the existing literature for accelerometer-measured physical activity among middle-aged and older adults with type 2 diabetes is lacking. OBJECTIVE: This study aims to identify research studies in which accelerometer-based cut points were used to classify the physical activity intensity of middle-aged to older adults with type 2 diabetes as sedentary, light, moderate, vigorous, and very vigorous, and to determine if validated accelerometer cut points specifically for this population exist. METHODS: We followed the Joanna Briggs Institute methodology for scoping reviews. Between June 23 and July 12, 2020, two reviewers independently screened records from four databases (PubMed, Web of Science, Embase, Engineering Village) and the ActiGraph Corp web site for eligible studies that included patients with type 2 diabetes with a sample mean age ≥50 years, used research-grade accelerometers, applied cut points to categorize objectively measured physical activity, and were available in English. We excluded studies reporting exclusively steps or step counts measured by accelerometers or pedometers and conference abstracts or other sources that did not have a full text available. Data extraction was completed using Microsoft Excel. Data for the following variables were tabulated based on frequency distributions: study design, accelerometer type, device placement, epoch length, total wear time, and cut points used. Study aims and participant demographic data were summarized. RESULTS: A total of 748 records were screened at the abstract level, and 88 full-text articles were assessed for eligibility. Ultimately, 46 articles were retained and analyzed. Participants' mean ages ranged from 50 to 79.9 years. The ActiGraph accelerometer and the Freedson et al and Troiano et al counts-per-minute cut points were the most frequently used across the literature. Freedson et al and Troiano et al counts-per-minute cut points for light, moderate, and vigorous activity correspond to <1952, 1952-5724, and ≥5725, and 100-2019, 2020-5998, and ≥5999, respectively. The Lopes et al cut points were developed by calibrating the ActiGraph in middle-aged and older adults with overweight/obesity and type 2 diabetes. These counts-per-minute thresholds are ≥200 (light), ≥1240 (moderate), and ≥2400 (vigorous), and were applied in 1 interventional study. CONCLUSIONS: An assortment of accelerometer cut points have been used by researchers to categorize physical activity intensity for middle-aged and older adults with diabetes. Only one set of cut points was validated and calibrated in our population of interest. Additional research is warranted to address the need for diabetes-specific cut points to inform public health recommendations. This includes confirmation that the Lopes et al cut points reflect clinically meaningful changes in physical activity for adults with diabetes who have comorbidities other than overweight/obesity and the development of relative intensity cut points that may be more suitable for those with suboptimal physical functioning.

Primary care patients' and providers' perspectives about an online weight management program integrated with population health management: Post-intervention qualitative results from the PROPS study.

Objective: To assess patients' and providers' attitudes about the online weight management program and population health management approach in the PROPS Study, which examined the effectiveness of these strategies in primary care. Methods: We conducted semi-structured interviews with 22 patients and nine providers. Using thematic analysis, we analyzed transcripts of the interviews to identify key themes. Results: Most patients found the online program to be well-structured and easy to use, although a few noted that the information was overwhelming or could be more personalized. Patients mentioned that the support from the population health managers was critical for their success, and several reported that they would have liked more involvement from their primary care provider or a dietitian. Providers also were satisfied with the interventions, and several stated that the population health management support was helpful because it added accountability. Providers suggested that the interventions could be improved by tailoring the information and integrating the online program with the electronic health record. Conclusion: Most patients and providers were satisfied with the interventions, with several recommendations for improvements. Innovation: These findings give additional information about patients' and providers' experience with this innovative approach for managing overweight and obesity in primary care.

Effect of an Online Weight Management Program Integrated With Population Health Management on Weight Change: A Randomized Clinical Trial.

Importance: Online programs may help with weight loss but have not been widely implemented in routine primary care. Objective: To compare the effectiveness of a combined intervention, including an online weight management program plus population health management, with the online program only and with usual care. Design, Setting, and Participants: Cluster randomized trial with enrollment from July 19, 2016, through August 10, 2017, at 15 primary care practices in the US. Eligible participants had a scheduled primary care visit and were aged 20 to 70 years, had a body mass index between 27 and less than 40, and had a diagnosis of hypertension or type 2 diabetes. Follow-up ended on May 8, 2019. Interventions: Participants in the usual care group (n = 326) were mailed general information about weight management. Participants in the online program only group (n = 216) and the combined intervention group (n = 298) were registered for the online program. The participants in the combined intervention group also received weight-related population health management, which included additional support from nonclinical staff who monitored their progress in the online program and conducted periodic outreach. Main Outcomes and Measures: The primary outcome was weight change at 12 months based on measured weights recorded in the electronic health record. Weight change at 18 months was a secondary outcome. Results: Among the 840 participants who enrolled (mean age, 59.3 years [SD, 8.6 years]; 60% female; 76.8% White), 732 (87.1%) had a recorded weight at 12 months and the missing weights for the remaining participants were imputed. There was a significant difference in weight change at 12 months by group with a mean weight change of -1.2 kg (95% CI, -2.1 to -0.3 kg) in the usual care group, -1.9 kg (95% CI, -2.6 to -1.1 kg) in the online program only group, and -3.1 kg (95% CI, -3.7 to -2.5 kg) in the combined intervention group (P < .001). The difference in weight change between the combined intervention group and the usual care group was -1.9 kg (97.5% CI, -2.9 to -0.9 kg; P < .001) and the difference between the combined intervention group and the online program only group was -1.2 kg (95% CI, -2.2 to -0.3 kg; P = .01). At 18 months, the mean weight change was -1.9 kg (95% CI, -2.8 to -1.0 kg) in the usual care group, -1.1 kg (95% CI, -2.0 to -0.3 kg) in the online program only group, and -2.8 kg (95% CI, -3.5 to -2.0 kg) in the combined intervention group (P < .001). Conclusions and Relevance: Among primary care patients with overweight or obesity and hypertension or type 2 diabetes, combining population health management with an online program resulted in a small but statistically significant greater weight loss at 12 months compared with usual care or the online program only. Further research is needed to understand the generalizability, scalability, and durability of these findings. Trial Registration: ClinicalTrials.gov Identifier: NCT02656693.

Integrating an online weight management program with population health management in primary care: Design, methods, and baseline data from the PROPS randomized controlled trial (Partnerships for Reducing Overweight and Obesity with Patient-centered Strategies).

BACKGROUND: Scalable, low-cost weight management strategies are needed in primary care. We conducted a pragmatic, cluster-randomized controlled trial to examine the effectiveness of an online weight management program integrated with population health management support. METHODS: We adapted an online weight management program and integrated it with population health management support in 15 primary care practices (24 clinics). We randomized the 24 clinics to usual care (UC), online program alone (OP), or combined intervention (CI). Eligible participants had to be ages 20 to 70 and have a recent primary care visit, body mass index (BMI) ≥ 27 and < 40 kg/m2, and a diagnosis of hypertension or type 2 diabetes. Participants attended routine visits and completed surveys over 18 months. The primary outcome is absolute weight change at 12 months (± 90 days) after enrollment, calculated from weights measured at primary care visits and recorded in the electronic health record. RESULTS: We enrolled 840 participants between July 2016 and August 2017 (326 UC, 216 OP, and 298 CI.) At enrollment, participants' mean age was 59.3 years, their mean weight was 203.1 pounds, and their mean BMI was 32.5 kg/m2; 60% of participants were female, 76.8% were white, 96.4% had hypertension, and 24.4% had type 2 diabetes. CONCLUSION: It is feasible to adapt an online weight management program and integrate it with population health management support in primary care. The results of this trial will provide valuable information about the effectiveness of these strategies in primary care settings. ClinicalTrials.govregistration number:NCT02656693.

Primary Care Patients' and Providers' Perspectives about an Online Weight Management Program: a Qualitative Study.

BACKGROUND: Primary care providers (PCPs) often take the lead role in caring for patients with overweight and obesity; however, few PCPs counsel patients about weight loss. Online weight management programs that are integrated within primary care may help address this gap in care. OBJECTIVE: To identify perceptions of and experience with online weight management programs in general and with a proposed online program, to identify barriers to use, and to improve the design and content of our intervention, which included an online program plus population health management (PHM) support from primary care practices. DESIGN: A mixed qualitative methods study including three patient focus groups and seven semi-structured interviews with healthcare providers. PARTICIPANTS: A total of 13 adult patients (age range, 20-70) with body mass index (BMI) 27-35 kg/m2 attended the focus groups. In-person semi-structured interviews were conducted with seven healthcare providers (three PCPs, two population health managers, one primary care nurse, and one registered dietitian). MAIN MEASURES: We developed and used semi-structured focus groups and interview guides. The focus group and interviews were recorded and transcribed. Using grounded theory, we analyzed the transcripts to identify and extract common concepts and themes. KEY RESULTS: Although patients and healthcare providers expressed positive opinions about online weight management programs, few patients had experience with them, and providers stated that such programs are not being widely implemented in primary care settings. Some participants highlighted the flexibility and low cost as strengths of online weight management tools compared with in-person programs. All participants had favorable opinions about our proposed intervention and were overwhelmingly positive about the combination of an online program and PHM support. CONCLUSIONS: This study highlights the potential value of online weight management programs and PHM support in primary care. CLINICAL TRIALS REGISTRATION: NCT02656693.