Diabetes mellitus (DM) is a serious and growing public health problem.¹ The prevalence and morbidity of DM are greater among older adults who often have multiple chronic morbidities.^2,3 Self-management skills are an essential means of reducing morbidity and health services use among older, comorbid patients with DM.^4,5 However, delivery of effective self-management education and support can be difficult in traditional primary care, even among patients who have access to care, medications, and DM educators but who also have persistently uncontrolled DM.⁶ Many primary care clinics have few personnel trained to effectively deliver self-management education and support for chronic DM care. Furthermore, DM self-management is often poorly integrated with the physician-patient encounter, and evidence-linking self-management activities and health outcomes are often indirect at best.^5,7

Objectives: To identify a taxonomy of health‐related values that frame goals of care of older, multimorbid adults who recently faced cancer diagnosis and treatment. Design: Qualitative analysis of data from a longitudinal cohort study of multimorbid cancer survivors. Setting: Cancer registries from regional Department of Veterans Affairs networks in New England and southeast Texas. Participants: Multimorbid adults who completed interviews 12 months after diagnosis of head and neck, colorectal, gastric, or esophageal cancer and after cancer treatment (N = 146). Measurements: An interdisciplinary team conducted thematic analyses of participants’ intuitive responses to two questions: Now that you have had cancer and may face ongoing decisions about medical care in the future, what would you want your family, friends, and doctors to know about you, in terms of what is most important to you in your life? If your cancer were to recur, is there anything you'd want to be sure your loved ones knew about you and your goals of care? Results: Analysis revealed five distinct health‐related values that guide how multimorbid cancer survivors conceptualize specific health care goals and medical decisions: self‐sufficiency, life enjoyment, connectedness and legacy, balancing quality and length of life, and engagement in care. Participants typically endorsed more than one value as important. Conclusion: Older multimorbid adults who recently faced life‐threatening cancer endorsed a multidimensional taxonomy of health‐related values. These health‐related values guide how they frame their goals for care and treatment preferences. Eliciting individuals’ sense of their values during clinical encounters may improve their experiences with health care and more effectively align treatments with goals of care.

Objectives: To develop a values‐based, clinically feasible process to help older adults identify health priorities that can guide clinical decision‐making. Design: Prospective development and feasibility study. Setting: Primary care practice in Connecticut. Participants: Older adults with 3 or more conditions or taking 10 or more medications (N=64). Intervention: The development team of patients, caregivers, and clinicians used a user‐centered design framework—ideate → prototype → test →redesign—to develop and refine the value‐based patient priorities care process and medical record template with trained clinician facilitators. Measurements: We used descriptive statistics of quantitative measures (percentage accepted invitation and completed template, duration of process) and qualitative analysis of barriers and enablers (challenges and solutions identified, facilitator perceptions). Results: We developed and refined a process for identifying patient health priorities that was typically completed in 35 to 45 minutes over 2 sessions; 64 patients completed the process. Qualitative analyses were used to elucidate the characteristics and training needed for the patient priorities facilitators, as well as perceived benefits and challenges of the process. Refinements based on our experience and feedback include streamlining the process for greater feasibility, balancing fidelity to the process while customizing to individuals, encouraging patients to share their priorities with their clinicians, and simplifying the template transmitted to clinicians. Conclusion: Trained facilitators conducted this process in a busy primary care practice, suggesting that patient priorities identification is feasible and acceptable, although testing in additional settings is necessary. We hope to show that clinicians can align care with patients' health priorities.

Background: The geriatric syndrome of frailty is one of the greatest challenges facing the U.S. aging population. Frailty in older adults is associated with higher adverse outcomes, such as mortality and hospitalization. Identifying precise early indicators of pre-frailty and measures of specific frailty components are of key importance to enable targeted interventions and remediation. We hypothesize that sensor-derived parameters, measured by a pendant accelerometer device in the home setting, are sensitive to identifying pre-frailty. Methods: Using the Fried frailty phenotype criteria, 153 community-dwelling, ambulatory older adults were classified as pre-frail (51%), frail (22%), or non-frail (27%). A pendant sensor was used to monitor the at home physical activity, using a chest acceleration over 48 h. An algorithm was developed to quantify physical activity pattern (PAP), physical activity behavior (PAB), and sleep quality parameters. Statistically significant parameters were selected to discriminate the pre-frail from frail and non-frail adults. Results: The stepping parameters, walking parameters, PAB parameters (sedentary and moderate-to-vigorous activity), and the combined parameters reached and area under the curve of 0.87, 0.85, 0.85, and 0.88, respectively, for identifying pre-frail adults. No sleep parameters discriminated the pre-frail from the rest of the adults. Conclusions: This study demonstrates that a pendant sensor can identify pre-frailty via daily home monitoring. These findings may open new opportunities in order to remotely measure and track frailty via telehealth technologies.

Background: Social isolation during COVID-19 may negatively impact older adults’ wellbeing. To assess its impact, we measured changes in physical activity and sleep among community-dwelling older adults, from pre-to post-pandemic declaration. Method: Physical activity and sleep in older adults (n = 10, age = 77.3 ± 1.9 years, female = 40%) were remotely assessed within 3-month pre-to 6-month post-pandemic declaration using a pendant-wearable system. Depression was assessed pre-and post-pandemic declaration using the Center for Epidemiologic Studies Depression scale and was compared with 48 h continuous physical activity monitoring data before and during pandemic. Results: Compared to pre-pandemic, post-pandemic time spent in standing declined by 32.7% (Cohen’s d = 0.78, p < 0.01), walking by 52.2% (d = 1.1, p < 0.01), step-counts by 55.1% (d = 1.0, p = 0.016), and postural transitions by 44.6% (d = 0.82, p = 0.017) with increase in sitting duration by 20.5% (d = 0.5, p = 0.049). Depression symptoms increased by 150% (d = 0.8, p = 0.046). Interestingly, increase in depression was significantly correlated with unbroken-prolong sitting bout (ρ = 0.677, p = 0.032), cadence (ρ = −0.70, p = 0.024), and sleep duration (ρ = −0.72, p = 0.019). Conclusion: This is one of the early longitudinal studies highlighting adverse effect of the pandemic on objectively assessed physical activity and sleep in older adults. Our observations showed need for timely intervention to mitigate hard to reverse consequences of decreased physical activity such as depression.

Mobile and tablet apps, ubiquitous and pervasive computing, wearable computing and domotics for health.