Barbara A. De La Cruz

BACKGROUND Diabetes self-management education and support (DSME/S) and diabetes group visits (DGV) improve outcomes for older adults but remain difficult to scale. Some digital technologies offer DSME/S content, but few are designed for the needs and preferences of older adults. OBJECTIVE We developed the Healthy Opportunities and Personal Empowerment (HOPE) App, an immersive digital health program, to deliver live, virtual DSME/S in a group visit format to older adults with type 2 diabetes (T2DM). Immersive technology allowed gamified, active learning programs to enhance self-management mastery. METHODS We conducted two phases of iterative HOPE App development and usability testing using a user-centered design process. Findings informed application revisions and updates. Two groups of patient advisors (PAG1, n=21, and PAG2, n=8) comprised of older adults with T2DM completed usability testing on the HOPE App prototype. Outcomes were assessed using scores from the System Usability Scale (SUS) and key informant interviews on user experience. Transcripts and observation notes were analyzed thematically RESULTS Highly valued HOPE App features include simplified navigation, avatar customization, self-paced tutorials, peer matching program, and immersive DSME/S content. Mean SUS scores increased from 71.0 in Phase 1 to 80.0 in Phase II. Participants highlighted the importance of intuitive navigation, large text, real-time voice communication, and peer interaction. Three user experience themes emerged: 1) identification with customized avatars, 2) social learning and immersive presence through peer discussion and mentorship, and 3) simulations and gamified training activities in the 3D virtual environment. Participants also identified barriers to the desired user experience, including limited avatar phenotypes, interference with voice communication, and tutorial navigation challenges. CONCLUSIONS User testing supported the usability of the HOPE App to deliver group-based, live action DSME/S with immersive technology. Findings highlight design priorities for scalable digital diabetes interventions tailored to older adults.

Background: Group-based diabetes care, both technology-enabled and in-person, can improve diabetes outcomes in low-income minority women, but the mechanism remains unclear. Objective: We tested whether diabetes group medical visits (GMVs) reduced hemoglobin A_1c (HbA_1c) by mitigating diabetes distress (DD), an emotional response affecting nearly half of adults with type 2 diabetes in community settings. Methods: We conducted a mediation and moderation analysis of data from the Women in Control 2.0 comparative effectiveness study, which showed that both technology-enabled and in-person diabetes GMVs improve HbA_1c. We tested whether DD mediated the relationship between diabetes GMV engagement and reductions in HbA_1c. We also tested whether this relationship was moderated by depressive symptoms and social support. Participants were 309 low-income and minority women. Diabetes GMV engagement was measured using the Group Climate Questionnaire. The mediator, DD, was measured using the Diabetes Distress Screening Scale. The outcome was the 6-month change in HbA_1c. Social support was measured using the Medical Outcomes Study Social Support Survey. Results: DD mediated the relationship between engagement and 6-month HbA_1c. Specifically, group engagement affected HbA_1c by reducing distress associated with the regimen of diabetes self-management (P=.04), and possibly the emotional burden of diabetes (P=.09). The relationship between engagement and 6-month HbA_1c was moderated by depressive symptoms (P=.02), and possibly social support (P=.08). Conclusions: Engagement in diabetes GMVs improved HbA_1c because it helped reduce diabetes-related distress, especially related to the regimen of diabetes management and possibly related to its emotional burden, and especially for women without depressive symptoms and possibly for women who lacked social support.

Background: The management of type 2 diabetes mellitus (T2DM) includes mastery of complex care activities, self-management skills, and routine health care encounters to optimize glucose control and achieve good health. Given the lifelong course of T2DM, patients are faced with navigating complex medical and disease-specific information. This health-seeking behavior is a driver of health disparities and is associated with hospitalization and readmission. Given that health-seeking behavior is a potentially intervenable social determinant of health, a better understanding of how people navigate these complex systems is warranted. Objective: To address this need, we aimed to develop new patient-reported outcome (PRO) measures that evaluate health-seeking behavior in persons with T2DM. These new PROs were designed to be included in the Re-Engineered Discharge for Diabetes-Computer Adaptive Test (REDD-CAT) measurement system, which includes several other PROs that capture the importance of social determinants of health. Methods: Overall, 225 participants with T2DM completed 56 self-report items that examined health-seeking behaviors. Classical Test Theory and Item Response Theory were used for measurement development. Exploratory factor analysis (EFA; criterion ratio of eigenvalue 1 to eigenvalue 2 being >4; variance for eigenvalue 1 ≥40%) and confirmatory factor analysis (CFA; criterion 1-factor CFA loading <.50; 1-factor CFA residual correlation >.20; comparative fit index ≥0.90; Tucker-Lewis index ≥0.90; root mean square error of approximation 4; variance for eigenvalue 1=41.4%-67.3%) and CFA (fit statistics all exceeded criterion values). This included (1) “Health-Seeking Behavior: PCP-Specific” (6 items); (2) “Health-Seeking Behavior: General Beliefs” (13 items); (3) “Health-Seeking Behavior: Family or Friends-Specific” (5 items); and (4) “Health-Seeking Behavior: Internet-Specific” (4 items). All items were devoid of differential item functioning for age, sex, education, or socioeconomic status factors. “Health-Seeking Behavior: General Beliefs” was developed to include both a computer adaptive test and a 6-item short form version; all other PROs were developed as static short forms. The psychometric reliability of these new PROs was supported; internal consistency ranged from acceptable to excellent (Cronbach α=.78-.91), and measures were free of significant floor or ceiling effects (floor effects range: 0%-8.9%; ceiling effects range: 0%-8.4%). Conclusions: The new REDD-CAT Health-Seeking Behavior PROs provide reliable assessments of health-seeking behaviors among those with T2DM.

BACKGROUND The management of type 2 diabetes mellitus (T2DM) includes mastery of complex care activities, self-management skills, and routine health care encounters to optimize glucose control and achieve good health. Given the lifelong course of T2DM, patients are faced with navigating complex medical and disease-specific information. This health-seeking behavior is a driver of health disparities and is associated with hospitalization and readmission. Given that health-seeking behavior is a potentially intervenable social determinant of health, a better understanding of how people navigate these complex systems is warranted. OBJECTIVE To address this need, we aimed to develop new patient-reported outcome (PRO) measures that evaluate health-seeking behavior in persons with T2DM. These new PROs were designed to be included in the Re-Engineered Discharge for Diabetes-Computer Adaptive Test (REDD-CAT) measurement system, which includes several other PROs that capture the importance of social determinants of health. METHODS Overall, 225 participants with T2DM completed 56 self-report items that examined health-seeking behaviors. Classical Test Theory and Item Response Theory were used for measurement development. Exploratory factor analysis (EFA; criterion ratio of eigenvalue 1 to eigenvalue 2 being >4; variance for eigenvalue 1 ≥40%) and confirmatory factor analysis (CFA; criterion 1-factor CFA loading <.50; 1-factor CFA residual correlation >.20; comparative fit index ≥0.90; Tucker-Lewis index ≥0.90; root mean square error of approximation 4; variance for eigenvalue 1=41.4%-67.3%) and CFA (fit statistics all exceeded criterion values). This included (1) “Health-Seeking Behavior: PCP-Specific” (6 items); (2) “Health-Seeking Behavior: General Beliefs” (13 items); (3) “Health-Seeking Behavior: Family or Friends-Specific” (5 items); and (4) “Health-Seeking Behavior: Internet-Specific” (4 items). All items were devoid of differential item functioning for age, sex, education, or socioeconomic status factors. “Health-Seeking Behavior: General Beliefs” was developed to include both a computer adaptive test and a 6-item short form version; all other PROs were developed as static short forms. The psychometric reliability of these new PROs was supported; internal consistency ranged from acceptable to excellent (Cronbach α=.78-.91), and measures were free of significant floor or ceiling effects (floor effects range: 0%-8.9%; ceiling effects range: 0%-8.4%). CONCLUSIONS The new REDD-CAT Health-Seeking Behavior PROs provide reliable assessments of health-seeking behaviors among those with T2DM.

BACKGROUND Group-based diabetes care, both technology-enabled and in-person, can improve diabetes outcomes in low-income minority women, but the mechanism remains unclear. OBJECTIVE We tested whether diabetes medical group visits (DMGVs) reduced hemoglobin A1c (A1c) by mitigating diabetes distress, an emotional response affecting nearly half of adults with type 2 diabetes in community settings. METHODS We conducted a mediation and moderation analysis of data from the Women in Control 2.0 (WIC2) comparative effectiveness study, which showed that both technology-enabled and in-person DMGVs improve A1c. We tested whether diabetes distress mediated the relationship between DMGV engagement and reductions in A1c. We also tested whether this relationship was moderated by depressive symptoms and social support. Participants were 309 low-income and minority women. DMGV engagement was measured using the Group Climate questionnaire (GCQ-S). The mediator, diabetes distress, was measured using the Diabetes Distress Scale (DDS-17). The outcome was the 6-month change in A1c (A1c). Social support was measured using the Medical Outcomes Study Social Support Survey. RESULTS Diabetes distress mediated the relationship between engagement and 6-month A1c. Specifically, group engagement affected A1c by reducing distress associated with the emotional burden of diabetes (P = 0.09) and the regimen of diabetes self-management (P = 0.04). The relationship between engagement and 6-month A1c was moderated by depressive symptoms (P = 0.02), and social support (P = 0.08). CONCLUSIONS Engagement in DMGVs improved A1c because it helped reduce diabetes-related distress, especially related to the regimen of diabetes management and its emotional burden, and especially for women without depressive symptoms and who lacked social support. CLINICALTRIAL ClinicalTrials.gov NCT02726425; https://clinicaltrials.gov/ct2/show/NCT02726425

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

Journal of Medical Internet Research - International Scientific Journal for Medical Research, Information and Communication on the Internet #Preprint #PeerReviewMe: Warning: This is a unreviewed preprint. Readers are warned that the document has not been peer-reviewed by expert/patient reviewers or an academic editor, may contain misleading claims, and is likely to undergo changes before final publication, if accepted, or may have been rejected/withdrawn. Readers with interest and expertise are encouraged to sign up as peer-reviewer, if the paper is within an open peer-review period. Please cite this preprint only for review purposes or for grant applications and CVs (if you are the author). 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 A_1c (HbA_1c) 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 HbA_1c ≥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 HbA_1c 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 HbA_1c 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

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.

BACKGROUND Incorporating physical activity in lifestyle routines is recommended for individuals living with type 2 diabetes. Accelerometer devices offer a promising alternative to self-report methods for measuring physical activity performance. However, the extant literature for accelerometer-measured physical activity among middle-aged/older adults with chronic conditions is lacking. OBJECTIVE We conducted a comprehensive scoping review of the literature to capture accelerometry methodologies in older adults with type 2 diabetes, specifically in relation to cutpoints that classify physical activity into intensity categories (sedentary, light, moderate, vigorous, very vigorous). METHODS Applying the Joanna Briggs Institute’s methodology, we searched PubMed, Web of Science, EMBASE, and Engineering Village to identify studies that used research-grade accelerometers to objectively measure physical activity intensity levels of adults with type 2 diabetes using cutpoints in participant samples of mean age 50 years and older. RESULTS We identified 46 studies that met our inclusion criteria. The ActiGraph was the most popular accelerometer among researchers, and the Freedson (1998) and Troiano (2008) cutpoints were favored the most. The Lopes (2009) cutpoints were developed by calibrating the ActiGraph accelerometer in middle-aged and older adults with overweight/ obesity and type 2 diabetes. Several studies noted limitations of accelerometry use that could lead to an underestimation or inaccurate representation of physical activity for our population of interest. Limitations included decreased accuracy due to variation in device placement and underestimation of activity intensity attributed to using cutpoints in older adults with lower fitness levels that were originally validated with younger adults. CONCLUSIONS Considering the high variability among accelerometry methodologies, more work needs to be done to understand activity intensity cut-offs for populations with a high burden of chronic disease, older age, and suboptimal physical functioning.