Use of Technologies at the Advanced Age

Diabetes Technology & TherapeuticsVol. 26, No. S1 Original ArticlesFree AccessUse of Technologies at the Advanced AgeSarah Sy, Alan Sinclair, Medha Munshi, Anna R. Kahkoska, Ruth Weinstock, and Tali Cukierman-YaffeSarah SyDivision of Geriatric Medicine, Department of Medicine, University of British Columbia, Vancouver, Canada.Search for more papers by this author, Alan SinclairFoundation of Diabetes Research in Older People (fDROP), London, UK.King's College, London, UK.Search for more papers by this author, Medha MunshiJoslin Diabetes Center, Boston, MA, USA.Beth Israel Deaconess Medical Center, Boston, MA, USA.Harvard Medical School, Boston, MA, USA.Search for more papers by this author, Anna R. KahkoskaDepartment of Nutrition, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.Division of Endocrinology and Metabolism, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.UNC Center for Aging and Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.Search for more papers by this author, Ruth WeinstockDepartment of Medicine, SUNY Upstate Medical University, Syracuse, NY, USA.Search for more papers by this author, and Tali Cukierman-YaffeDivision of Endocrinology, Diabetes and Metabolism, Sheba Medical Center, Ramat Gan, Israel.Department of Epidemiology and Preventive Medicine, School of Public Health, Faculty of Medicine, Tel-Aviv University, Tel Aviv, Israel.Search for more papers by this authorPublished Online:1 Mar 2024https://doi.org/10.1089/dia.2024.2511AboutSectionsPDF/EPUB Permissions & CitationsPermissionsDownload CitationsTrack CitationsAdd to favorites Back To Publication ShareShare onFacebookXLinked InRedditEmail IntroductionDiabetes is a major public health burden associated with high mortality, morbidity, hospitalization, a reduction in quality of life, and increased rates of health-care services utilization (1). Healthy aging with diabetes is a challenge. It is a challenge for health-care systems due to the high prevalence of the disease in older age (∼25% of the population over age 65) (2), and it is a challenge for health-care providers, patients, family, and other care providers because it is a disease that requires elaborate self-care management capacities. Diabetes may be viewed as a disease of accelerated aging because it is a risk factor for cognitive dysfunction (3), dementia (4–6), depression (7), physical disability, frailty, and sarcopenia (8–14). These impede self-care management capacities such as insulin scheduling, the ability to alter the treatment regimen according to differing life situations, and dealing with hypoglycemia events (and prevention of deterioration to severe hypoglycemia) (2,15,16). Cognitive dysfunction, dementia, physical disability, and frailty are now considered long-term complications of the disease, and treatment is targeted at slowing their progression.Current technology has an important role in glucose management and avoiding hypoglycemia, and it may also have a role in reducing diabetes-related complications, slowing functional decline, and enhancing quality of life. Technology may also play a role in many other aspects of diabetes care in older people that are not necessarily directly related to glucose control. In order to best serve older adults, technology needs to be adapt to address the challenges that develop with aging and the changing needs due to the development or progression of comorbidities or loss of function. Thus, future technology may also have an important role in setting treatment targets according to functional/cognitive state (as recommended currently by many professional organizations), enhancing self-care capacity, and alleviating functional and cognitive dysfunction in this population.The current article provides an overview of articles published in the last year regarding the use of technology in older people with diabetes. Six International Geriatric Diabetes Society (IDGS) members (the authors of this article) participated in the process, which included several stages: (1) discussion and decision on topic areas; (2) initial and secondary screening of articles and decisions about which articles to include; and (3) summary of articles and commentary according to topic areas. The initial broad search pertained to the use of continuous glucose monitoring (CGM), pumps, hybrid closed-loop systems, insulin pens, and other devices by older people with diabetes. It also included articles related to the use of telehealth and artificial intelligence (AI) in this population.The initial search produced 746 titles and abstracts. Two of the authors (TCY, SY) went over the initial list and produced a shorter list from which all team members chose. The final list consists of 15 original articles pertaining to the following topic areas: (1) hybrid closed-loops in older people with diabetes, (2) insights into patient and caregiver experiences using CGM, (3) long-term and differential impacts of CGM use in older adults with type 1 diabetes (T1D), (4) use of AI for improving the care of older people with diabetes, (5) real-world evidence regarding CGM use in older adults, (6) telehealth in older people with diabetes, and (7) technology, sarcopenia, frailty, and glucose.Key Articles ReviewedClosed-Loop Insulin Delivery versus Sensor-augmented Pump Therapy in Older Adults with Type 1 Diabetes (ORACL): A Randomized, Crossover TrialMcAuley SA, Trawley S, Vogrin S, Ward GM, Fourlanos S, Grills CA, Lee MH, Alipoor AM, O'Neal DN, O'Regan NA, Sundararajan V, Colman PG, MacIsaac RJDiabetes Care2022; 45:381–390Hybrid Closed-Loop Glucose Control Compared with Sensor Augmented Pump Therapy in Older Adults with Type 1 Diabetes: An Open-label Multicenter, Multinational, Randomized, Crossover StudyBoughton CK, Hartnell S, Thabit H, Mubita WM, Draxlbauer K, Poettler T, Wilinska ME, Hood KK, Mader JK, Narendran P, Leelarathna L, Evans ML, Hovorka RLancet Healthy Longevity2022; 3:e135–e142Patient-reported Outcomes for Older Adults on CamAPS FX Closed Loop SystemSchneider-Utaka AK, Hanes S, Boughton CK, Hartnell S, Thabit H, Mubita WM, Draxlbauer K, Poettler T, Hayes J, Wilinska ME, Mader JK, Narendran P, Leelarathna L, Evans ML, Hovorka R, Hood KKDiabet Med2023; 40:e15126Continuous Glucose Monitoring with Data Sharing in Older Adults: A Qualitative StudyAllen NA, Grigorian EG, Mansfield K, Berg CA, Litchman MLJ Clin Nurs. Published online June 22, 2023. doi: 10.1111/jocn.16808"Nothing Is Linear": Characterizing the Determinants and Dynamics of CGM Use in Older Adults with Type 1 DiabetesKahkoska AR, Smith C, Thambuluru S, Weinstein J, Batsis JA, Pratley R, Weinstock RS, Young LA, Hassmiller Lich KDiabetes Res Clin Pract2023; 196:110204Estimation of a Machine Learning–based Decision Rule to Reduce Hypoglycemia among Older Adults with Type 1 Diabetes: A Post Hoc Analysis of Continuous Glucose Monitoring in the WISDM StudyKahkoska AR, Shah KS, Kosorok MR, Miller KM, Rickels M, Weinstock RS, Young LA, Pratley REJ Diabetes Sci Technol. Published online January 11, 2023. doi: 10.1177/19322968221149040Benefit of Continuous Glucose Monitoring in Reducing Hypoglycemia Is Sustained through 12 Months of Use among Older Adults with Type 1 DiabetesMiller KM, Kanapka LG, Rickels MR, Ahmann AJ, Aleppo G, Ang L, Bhargava A, Bode BW, Carlson A, Chaytor NS, Gannon G, Goland R, Hirsch IB, Kiblinger L, Kruger D, Kudva YC, Levy CJ, McGill JB, O'Malley G, Peters AL, Philipson LH, Philis-Tsimikas A, Pop-Busui R, Salam M, Shah VN, Thompson MJ, Vendrame F, Verdejo A, Weinstock RS, Young L, Pratley R for the WISDM Study GroupDiabetes Technol Ther 2022;24:424–434Engagement in Digital Health App-based Prevention Programs Is Associated with Weight Loss among Adults Age 65+Auster-Gussman LA, Lockwood KG, Graham SA, Pitter V, +Branch OHFront Digit Health 2022;4:886783Human Digital Twin for Personalized Elderly Type 2 Diabetes ManagementThamotharan P, Srinivasan S, Kesavadev J, Krishnan G, Mohan V, Seshadhri S, Bekiroglu K, Toffanin CJ Clin Med 2023;12:2094Reduced Acute Diabetes Events after FreeStyle Libre System Initiation in People 65 Years or Older with Type 2 Diabetes on Intensive Insulin Therapy in FranceGuerci B, Levrat-Guillen F, Vicaut E, De Pouvourville G, Detournay B, Emery C, Riveline J-PDiabetes Technol Ther 2023;25:384–394Initiation of Continuous Glucose Monitoring Is Linked to Improved Glycemic Control and Fewer Clinical Events in Type 1 and Type 2 Diabetes in the Veterans Health AdministrationReaven PD, Newell M, Rivas S, Zhou X, Norman GJ, Zhou JJDiabetes Care 2023;46:854–863Use of Telemedicine in Adults with Type 1 Diabetes: Do Age and Use of Diabetes-related Technology Matter?Toschi E, Adam A, Atakov-Castillo A, Slyne C, Laffel L, Munshi MTelemed J E Health 2023;29:1374–1382A Web-delivered, Clinician-led Group Exercise Intervention for Older Adults with Type 2 Diabetes: Single-arm Pre-Post InterventionKirwan, M, Chiu CL, Laing T, Chowdhury N, Gwynne KJ Med Internet Res 2022;24:e39800The Association between Glucose Fluctuation with Sarcopenia in Elderly Patients with Type 2 Diabetes MellitusMa G-C, Zou L-L, Dai W, Wang Z-Z, Cao Y-HEur Rev Med Pharmacol Sci 2023;27:1912–1920A Behavioral Lifestyle Intervention to Improve Frailty in Overweight or Obese Older Adults with Type 2 Diabetes: A Feasibility StudyJiwani R, Wang J, Li C, Dennis B, Patel D, Gelfond J, Liu Q, Siddiqui N, Bess C, Monk S, Serra M, Espinoza SJ Frailty Aging 2022;11:74–82HYBRID CLOSED-LOOPS IN OLDER PEOPLE WITH DIABETESClosed-Loop Insulin Delivery versus Sensor-augmented Pump Therapy in Older Adults with Type 1 Diabetes (ORACL): A Randomized, Crossover TrialMcAuley SA1,2, Trawley S1,3, Vogrin S1, Ward GM1,2, Fourlanos S1,4, Grills CA1,2, Lee MH1,2, Alipoor AM1,2, O'Neal DN1,2, O'Regan NA5, Sundararajan V1,6, Colman PG1,4, MacIsaac RJ1,21Department of Medicine, University of Melbourne, Melbourne, Australia; 2Department of Endocrinology & Diabetes, St Vincent's Hospital Melbourne, Melbourne, Australia; 3Department of Psychology, Cairnmillar Institute, Melbourne, Australia; 4Department of Diabetes and Endocrinology, The Royal Melbourne Hospital, Melbourne, Australia; 5Department of Geriatric Medicine, Waterford Integrated Care for Older People, University Hospital Waterford, Waterford, Ireland; 6Department of Public Health, La Trobe University, Melbourne, AustraliaDiabetes Care 2022;45:381–390The efficacy and safety of closed-loop insulin delivery as compared with sensor-augmented pump (SAP) therapy were examined among older adults with type 1 diabetes (T1D).MethodsThis open-label, randomized (1:1), crossover trial compared 4 months of closed-loop versus SAP therapy. Eligible adults were aged ≥ 60 years, with T1D (duration ≥ 10 years) and using an insulin pump. At baseline the participants underwent an assessment for sarcopenia, frailty, and functional and cognitive status: 20% had cognitive deficits (Montreal Cognitive Assessment score < 26), 20% were prefrail, 30% had hypoglycemia unawareness, and 13% had had two or more severe hypoglycemic events in the past year. As part of the crossover design, individuals were randomized to either the MiniMed hybrid closed-loop system (G670) first or to SAP therapy first using the MiniMed G670 in manual mode for 4 months, after which the individuals were switched to the alternate system. The primary outcome was continuous glucose monitoring (CGM) time in range (3.9–10.0 mmol/L).ResultsThe 30 participants (mean age 67 ± 5 SD years), who had a median T1D duration of 38 years (IQR, 20–47), were randomized as 15 to each arm, and all completed the trial. The mean time in range was 75.2% ± 6.3% SD during the closed-loop stage and 69.0% ± 9.1% SD during the SAP stage (difference of 6.2 percentage points [95% CI, 4.4–8.0]; P < 0.0001). All prespecified CGM metrics favored closed loop over the SAP, and the benefits were greatest overnight. Closed loop reduced CGM time by < 3.9 mmol/L during 24 hours/day by 0.5 percentage points (95% CI, 0.3–1.1; P = 0.0005) and overnight by 0.8 percentage points (0.4–1.1; P < 0.0001) compared with SAP. No significant difference was found in hemoglobin A1c (HbA1c) in comparing the closed-loop and SAP stages (7.3% [IQR, 7.1–7.5] (56 mmol/mol [IQR, 54–59]) vs. 7.5% (IQR, 7.1–7.9) (59 mmol/mol [IQR, 54–62]), respectively; P = 0.13). The closed-loop stage had three severe hypoglycemia events, and the SAP stage had two; none required hospitalization. The SAP stage had one episode of diabetic ketoacidosis, and the closed-loop stage had no serious adverse events.ConclusionsFor older adults with long-duration T1D, closed-loop therapy is an effective treatment option that reduced the time spent in the hypoglycemic range overnight, with no safety issues identified. In this study, the older adults using closed-loop therapy had higher time in range and less time below range compared with SAP therapy.Hybrid Closed-Loop Glucose Control Compared with Sensor Augmented Pump Therapy in Older Adults with Type 1 Diabetes: An Open-label Multicenter, Multinational, Randomized, Crossover StudyBoughton CK1,2, Hartnell S2, Thabit H3,4, Mubita WM3, Draxlbauer K5, Poettler T6, Wilinska ME1, Hood KK7, Mader JK6, Narendran P5,8, Leelarathna L3,4, Evans ML1,2, Hovorka R11Wellcome-MRC Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, UK; 2Cambridge University Hospitals NHS Foundation Trust, Wolfson Diabetes and Endocrine Clinic, Cambridge, UK; 3Diabetes, Endocrinology and Metabolism Centre, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK; 4Division of Diabetes, Endocrinology and Gastroenterology, Faculty of Biology, Medicine and Health, University of Manchester, UK; 5University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK; 6Division of Endocrinology and Diabetology, Department of Internal Medicine, Medical University of Graz, Austria; 7Korey K Hood, Division of Pediatric Endocrinology, Stanford University, Stanford Diabetes Research Center, CA; 8Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UKLancet Healthy Longevity 2022;3:e135–e142The distinct characteristics of older adults with type 1 diabetes (T1D) make optimizing glycemic control challenging, and hybrid closed-loop glucose control may be safer and more effective for this group than sensor-augmented pump (SAP) therapy.MethodsIn an open-label, multicenter, multinational (UK and Austria), randomized, crossover study, adults aged 60 years and older with T1D using insulin pump therapy underwent two 16-week periods in random order to compare hybrid closed-loop (CamAPS FX) with SAP therapy. Block randomization by means of central randomization software to one of two treatment sequences was stratified by center. The primary end point was the proportion of time sensor glucose was in target range between 3.9 and 10.0 mmol/L. Analysis for the primary end point and adverse events was by intention to treat.ResultsOf the 38 participants enrolled in the study, one withdrew during run-in because of difficulties with the study pump infusion sets. The characteristics of the remaining 37 participants were median age 68 (IQR, 63–70) years; mean baseline glycated hemoglobin (HbA1c); 7.4% ± 0.9% SD; 57 ± 10 mmol/mol SD. Between September 4, 2019, and October 2, 2020 the participants were randomly assigned to the study arms. The proportion of time with glucose between 3.9 and 10.0 mmol/L was significantly higher in the closed-loop group compared with the SAP group: 79.9% ± 7.9% SD versus 71 · 4% ± 13.2% SD (difference 8.6 percentage points [95% CI, 6.3–11.0], P < 0.0001). During the SAP period, two severe hypoglycemia events occurred as well as two non-treatment-related serious adverse events associated with COVID-19.ConclusionsHybrid closed-loop insulin delivery is safe and achieves superior glycemic control compared with SAP therapy in older adults with long duration of T1D without increasing the risk of hypoglycemia. Hybrid closed-loop therapy may be a clinically important treatment option for older adults with T1D.Patient-reported Outcomes for Older Adults on CamAPS FX Closed Loop SystemSchneider-Utaka AK1, Hanes S1, Boughton CK2,3, Hartnell S3, Thabit H4,5, Mubita WM4, Draxlbauer K6, Poettler T7, Hayes J2, Wilinska ME2, Mader JK7, Narendran P6,8, Leelarathna L4,5, Evans ML2,3, Hovorka R2, Hood KK11Division of Endocrinology and Diabetes, Stanford Diabetes Research Center, University, Stanford, CA; 2Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK; 3Wolfson Diabetes and Endocrine Clinic, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK; 4Diabetes, Endocrinology and Metabolism Centre, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK; 5Division of Diabetes, Endocrinology and Gastroenterology, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK; 6University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK; 7Division of Endocrinology and Diabetology, Department of Internal Medicine, Medical University of Graz, Graz, Austria; 8Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UKDiabet Med 2023;40:e15126Use of the hybrid closed-loop (HCL) system is associated with improved time in range and glycated hemoglobin A1c across the age span, but little is known about its effects on patient-reported outcomes.MethodsThis open-label, randomized, multisite study compared HCL (CamAPS FX) to sensor-augmented pump (SAP) in a sample of older adults (≥ 60 years) with type 1 diabetes (T1D). Thirty-five older adults completed the patient-reported outcome surveys at the start of the study and after each period of 16 weeks using either HCL or SAP. At the end of the study, 19 participated in interviews about their experiences with HCL.ResultsOn the Glucose Monitoring Satisfaction Survey after 16 weeks of HCL use, improvement was seen in the overall Diabetes Distress Scale score; the two subscales (powerlessness and physician distress) improved significantly along with trust. The user experience interview responses were consistent in noting the benefits of improved glycemic control and worrying less about diabetes.ConclusionsPatient-reported outcomes and subjective user experiences all showed improvements after using HCL in this sample of older adults with T1D.CommentsWith the aging of the population and improvements in the care of people living with T1D, the prevalence of type 1 diabetes over the age of 60 is growing. This poses new challenges. First, hypoglycemia unawareness in more prevalent among older people; second, as frail and prefrail states become more prevalent in older age, the consequences of severe hypoglycemia events such as falls can be quite detrimental. Finally, cognitive impairment also is more prevalent in the older age group, which poses a real challenge to managing the complex insulin regimen required from people with T1D.Hybrid closed-loop systems in older adults living with T1D, over and beyond achieving better glucose control, have the potential to almost eliminate hypoglycemia as an event in this age group. This in turn may reduce the rate of adverse effects such as falls. For individuals with cognitive impairment, hybrid closed-loop systems provide a simpler method to manage their insulin regimen. In the last year, two randomized, crossover trials that focused on the effect of hybrid closed loops in older people with T1D (≥ 60 years) have been published.The Older Adults Closed Loop Trial (ORACL), a two-center Australian study, included 30 individuals with T1D. The authors reported improvements in time in range, time above range, and time below range, with no effect on patient-reported outcomes nor on cognitive function or frailty measures. Although the participants reported feeling largely positive about the closed-loop system, the Minimed G670 system (unlike the current MiniMed G780) does have many alerts, which may account for their reduction in positivity at the trial's end compared with baseline.The second trial, an open-label, multicenter, multinational (UK and Austria), randomized, crossover study included people with T1D aged 60 years and older and compared hybrid closed-loop (CamAPS FX) with sensor-augmented pump (SAP) therapies over a period of 16 weeks. Although Boughton and colleagues performed no screening for impairments in dexterity, vision, hearing, or cognition, they noted that their inclusion criteria—good knowledge of insulin pump use—would have precluded individuals with substantial impairments. The authors reported an increase in time in range and a decrease in the time spent with glucose values above 16.7 mmol/L; they did not find a difference in the time below range. A second article from this trial focused on patient-reported outcomes. Significant improvements were noted in the Diabetes Distress Scale score and in the powerlessness and physician distress subscales, as well as an improvement in trust on the Glucose Monitoring Satisfaction Survey.These studies highlight several important points. First, in the era of hybrid closed-loop technology, the concept that aiming for lower time below range equates to lower time in range may be misleading. This raises the question of whether it is time to rethink the current guidelines for percentage of time in range for older people with diabetes. Second, these systems have the potential to change what is most important in older age: quality of life. Third, even in individuals with cognitive deficits and prefrail states the system has proved to be safe and have high efficacy. Given the growing challenge of treating older people with cognitive deficits on complex insulin regimes, the hybrid closed-loop systems and possibly the closed-loop system may provide a solution to a growing unmet need in this population.INSIGHTS INTO PATIENT AND CAREGIVER EXPERIENCES USING CGMContinuous Glucose Monitoring with Data Sharing in Older Adults: A Qualitative StudyAllen NA1, Grigorian EG1, Mansfield K1, Berg CA2, Litchman ML31University of Utah, College of Nursing, Salt Lake, UT; 2Department of Psychology, University of Utah, Salt Lake, UT; 3Utah Diabetes and Endocrinology Center, University of Utah, College of Nursing, Salt Lake, UTJ Clin Nurs. Published online June 22, 2023. doi: 10.1111/jocn.16808The SHARE Plus intervention educates individuals with type 1 diabetes (T1D) and their care partners about communication strategies, problem-solving strategies, and action planning when using continuous glucose monitoring (CGM) with a smartphone data-sharing app that provides glucose data and alerts. This study examined the users' perceptions of the SHARE Plus intervention and its effects on communication, collaboration, and involvement in day-to-day diabetes management.MethodsIn this qualitative descriptive study, 10 older adults with T1D wore a CGM for 3 months, and their care partners (n = 10) used the data-sharing app. The SHARE Plus educational component consisted of one 90-minute session, and after the 12-week study semistructured interviews were conducted across 10 dyads (person with diabetes and care partner). The interviews were transcribed, coded, and analyzed for common themes, and a qualitative description and constant comparison approach were used to examine the similarities and differences in the participants' experiences.ResultsAcross the participant dyads, the SHARE Plus intervention increased diabetes knowledge, improved confidence, and helped partners understand how to navigate symptoms and behaviors and know when to intervene. The dyads successfully worked together to optimize diabetes management through improved communication, collaboration, and management of disagreements. The majority of the participants with diabetes and their care partners reported no conflicts in communication, but disagreements about diabetes management did occur with some dyads. From a psychological perspective, the SHARE Plus intervention impacted care partners in various ways: the live-in care partners felt peace of mind, but the care partners who lived away from the persons with T1D felt increased worry and concern.ConclusionsThe SHARE Plus intervention may be useful to guide future development in diabetes dyadic care and education interventions."Nothing Is Linear": Characterizing the Determinants and Dynamics of CGM Use in Older Adults with Type 1 DiabetesKahkoska AR1,3,5, Smith C2, Thambuluru S3, Weinstein J2, Batsis JA1,4,5, Pratley R6, Weinstock RS7, Young LA3, Hassmiller Lich K31Department of Nutrition, University of North Carolina at Chapel Hill, Chapel Hill, NC; 2Department of Health Policy and Management, University of North Carolina at Chapel Hill, Chapel Hill, NC; 3Division of Endocrinology and Metabolism, University of North Carolina at Chapel Hill, Chapel Hill, NC; 4Division of Geriatric Medicine, Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC; 5Center for Aging and Health, School of Medicine, University of North Carolina at Chapel Hill, NC; 6AdventHealth Translational Research Institute, Orlando, FL; 7SUNY Upstate Medical University, Syracuse, NYDiabetes Res Clin Pract 2023;196:110204Continuous glucose monitoring (CGM) can reduce hypoglycemia in older adults with type 1 diabetes (T1D). This study characterized the factors that influence effective use among older adults.MethodsOlder adults with type T1D (age ≥ 65) and their caregivers were recruited via the University of North Carolina at Chapel Hill outpatient diabetes clinic. Older adults living with T1D were ≥ 65 years of age at the time of recruitment, used any type of insulin regimen of pump or multiple daily injections, were able to manage their diabetes independently or with the help of a caregiver, had a hemoglobin A1c (HbA1c) of ≤ 10.0 % (86 mmol/mol), comprehended written and spoken English, and were vaccinated for COVID-19. After they had completed questionnaires on their baseline characteristics, daily smartphone use, and experiences with CGM, they participated in a series of nine parallel participatory workshops that used drawing and scripted activities to construct a model of the system structure underlying their common CGM use patterns, followed by focus group discussions. The resulting data were synthesized in a qualitative model of the hypothesized system of factors producing distinct patterns of CGM use in older adults. The model was validated through virtual follow-up interviews.ResultsData were collected from 33 participants (four patient–caregiver dyads, mean age 73.8 ± 4.4 years [range, 66–85 years]; 16% non-CGM users, and 79% pump users). The system model based on the workshops delineates the drivers of CGM uptake, the drivers of ongoing CGM use, and the feedback loops that either reinforce or counteract future CGM use. The participants emphasized the importance of different sets of feedback loops at different points in the duration of CGM use.ConclusionsBoth individualized and dynamic factors and feedback loops drive effective CGM use in older adults, which suggests opportunities for staged and tailored age-specific education and support.CommentsThese studies together apply qualitative research methodology to provide rich insight into the lived experience of older adults with T1D and their care partners while using CGM as part of diabetes management. Kahkoska and colleagues engaged 33 older adults, including 29 persons living with T1D and four care partners, in a participatory systems science approach to develop a model of the system of factors and their feedback loops that interact to shape the trajectory of CGM use over time. Their data show that different barriers to effective use of CGM arise across the stages of learning and usage, indicating there are high-leverage points for interventions to promote sustained, effective CGM use.The study by Allen and colleagues used a semistructured interviewing approach to elicit the experiences of 10 older adult dyads (one person living with diabetes and a care partner) after they had participated in an intervention in which the older adults with diabetes wore a CGM and their care partners used a data-sharing app. The authors reported multiple positive effects of the data-sharing educational intervention—improved diabetes knowledge, confidence, and communication skills to work collaboratively to optimize diabetes management—as well as some within-dyad concerns and disagreements.Together, these studies provide a window into the complex, heterogeneous experiences that older adults and their care partners may have as they learn to incorporate new technology like CGM into their long-term self-management regimens. The results underscore the importance of age-specific education surrounding diabetes technology, including the role of materials to help with the early challenges as well as those that arise later in the learning process. Care partner integration and holistic support can maximize benefits of these technologies. The richness of these data invites future research to continue to center the voices of older adults and their care partners in the development of age-specific, patient-centered interventions to support the adoption of evidence-based diabetes technology.LONG-TERM AND DIFFERENTIAL IMPACTS OF CGM USE IN OLDER ADULTS WITH TYPE 1 DIABETESEstimation of a Machine Learning–based Decision Rule to Reduce Hypoglycemia among Older Adults with Type 1 Diabetes: A Post Hoc Analysis of Continuous Glucose Monitoring in the WISDM StudyKahkoska AR1,2, Shah KS3, Kosorok MR3, Miller KM4, Rickels M5, Weinstock RS6, Young LA7, Pratley RE81Department of Nutrition, University of North Carolina at Chapel Hill, Chapel Hill, NC; 2UNC Center for Aging and Health, University of North