Caregiving and COVID-19: Perspectives from a Care Coach

Family caregivers of community-dwelling older adults have faced unprecedented caregiving challenges during the COVID-19 pandemic. Examining the accumulated impact on family caregivers can help health and aging service providers design resources and supports that are resilient to emergency situations, and reduce negative psychological and physical consequences and risk of abuse within caregiving dyads. Data was collected as part of a pilot intervention in which “Care Coaches” provided telephonic coaching sessions to family caregivers of older adults. We examined Care Coach observations documented after coaching sessions with 24 family caregivers between March 2020 and February 2021. Two coders employed thematic analysis to generate codes and themes. The sample was 70% female, 80% were the spouse or significant other of their care receiver, the mean age was 61, and 53% were Non-Hispanic White. Themes and sub-themes included: (1) increased caregiver burden and diminished care networks due to fear of exposure to or contraction of COVID-19, (2) barriers to accessing in-home personal assistance services and home-delivered meals despite intervention efforts, and (3) the exacerbation of caregiver social isolation due to COVID-19 lockdown policies. Findings highlight the ways in which COVID-19 has amplified caregiver burden through the breakdown of formal and informal support systems. Potential adaptations of community-based services for older adults and their caregivers include remote service liaisons and need assessment of caregiver dyads to assure access to home-based personal assistance services and nutrition support for those at greatest risk of negative consequences during emergency service lapses.

Home-based exercise program for older adults with Motoric Cognitive Risk syndrome: feasibility study

Aim: We developed a home-based goal-directed exercise program with telephonic coaching to overcome barriers to exercise participation in cognitively impaired older adults. Methods: Six patients with Motoric Cognitive Risk syndrome at high risk for dementia were enrolled, three assigned to goal-directed exercises and three to stretching exercises. All participants underwent an in-person training session followed by a session at home with a telephonic coach. Sessions were supervised by a physiatrist, and exercise programs were personalized. Results: In-person training and remote telephonic coaching support promoted adherence. There were no adverse effects and interventions were rated highly. Participant and logistical barriers were identified that can inform design of home-based clinical trials. Conclusion: Home-based exercises are safe and feasible in older adults with Motoric Cognitive Risk.

Engagement in a Multi-Feature Digital Health Lifestyle Change Program as a Predictor of Weight Loss

Background: Modern digital health interventions targeting weight loss employ multiple evidence-based strategies, including nutrition tracking, coaching, and activity monitoring, providing users with choice as they set and achieve their own goals. Still, limited research exists on the partial effects of each component of such interventions, and whether participants choose to use all of the features of a program. The objective of this study was to test the individual components of a fully-featured digital health lifestyle intervention as predictors of weight loss in a single statistical model. Methods: Participants in the study (N=25,273) were enrolled in the Livongo for Weight Loss program as part of their employee wellness benefit across 57 states/territories of the US from April, 2019 to January, 2021. Participants received a cellular-connected scale to use daily in the program; they were asked to track their eating via the app and physical activity via smartphones or wearables. Additionally, participants could engage with coaches voluntarily or by receiving feedback from coaches on their recorded food logs. A mixed-effects generalized linear model was used to test the effects of scale usage, physical activity, human telephonic coaching, and food logs without and without coaching feedback on the percent weight loss the following month. Predictors were disaggregated into between- and within-subject components to understand the impact of each component relative to one’s own mean. The month in the program and whether or not that month occurred during the COVID-19 pandemic were entered as time-varying covariates. Baseline age, gender, and BMI were entered as time-invariant covariates. Results: Participants were 45% male and had average age of 54.3 years old (SD =11.4), with an average BMI of 33.10 kg/m2 (SD: 6.2). On average, participants were enrolled in the program for 10.4 months (SD: 5.1). Each additional use of the scale above one’s own average was associated with an overall 7.4% weight loss (z=21.06,p<0.001). Similarly, each additional minute of moderate-vigorous physical activity (MVPA) above one’s own average was associated with an overall 2.4% weight loss (z=3.14, p<0.01). Lastly, coaching and food logging with coaching feedback at a frequency above one’s own average were associated with approximately a 6% weight loss throughout the program (z=3.08 and 2.35, respectively; p<0.05 for both). Conclusion: We found that frequency of use of a scale in a weight loss intervention was most predictive of weight loss, followed by human coaching interaction and physical activity. However, food logging without feedback did not significantly impact weight loss among participants. Additional work is needed to understand drivers associated with increased utilization of beneficial program features, including optimizing the use of coaching, which offers great benefit, but may be costly to scale.

Examining Changes in Healthy Days After Health Coaching

Purpose: To describe changes in health-related quality of life (HRQOL) related to variation in demographic characteristics, program goals, and program participation, among health coaching program participants. Design: A retrospective observational study of a health coaching program. Setting and Participants: A total of 2169 adults enrolled in an individually purchased or employer-sponsored health plan from a large health and well-being company, who participated in a health coaching program between January 2016 and April 2017. Intervention: The health coaching program used evidence-based behavior change strategies to encourage skill development, self-monitoring, and goal setting/achievement. Health coaching program modalities included online and telephonic coaching sessions. Measures: Demographic characteristics (gender, age, race, income), goal categories (weight management, fitness, nutrition, stress management, other), program modality (online, telephonic, both), engagement level (low, medium, high), and Healthy Days, a validated HRQOL measure developed by the Centers for Disease Control and Prevention. Analysis: t Tests, mixed analysis of variance (ANOVA). Results: There were significant ( P < .05) reductions in average total unhealthy days (UHDs) across all goal categories. Mixed ANOVAs identified a significant main effect for time, for all demographic characteristics ( P values < .05), and a significant effect for program modality ( P < .0001), time ( P < .0001), and interaction effects, between program modality and time, on average UHD ( P = .01). Conclusion: Our findings indicate significant reductions in UHD, following 6 months of health coaching, and support the use of HRQOL measures, which are known to be highly correlated with traditional measures of health, to evaluate health coaching programs.