Phatak, Vaishali

Abstract Physical inactivity is a modifiable risk factor for Alzheimer’s Disease and Related Dementias (ADRD) that can be remediated using remotely delivered interventions. The 12-week telerehabilitation physical activity behavioral (TPAB) intervention includes receipt of a wearable sensor and weekly discussions about physical activity self-monitoring, goal setting, facilitators, and barriers. TPAB has been shown to be feasible and efficacious in increasing daily steps in older adults. However, evidence is lacking for TPAB’s use for people with MCI and using a dyadic approach (i.e., with their care partners). Results from the first phase of our study include descriptive information from two dyads about (1) dyad member interaction with the wearable sensor (i.e., how knowing the current daily step count impacted activity), (2) how dyad members helped each other overcome individual or shared barriers to daily stepping and (3) how dyad members planned activities together to achieve high daily average stepping. This project quantitatively identified (1) the highest stepping day each week was the same for both dyad members 46% of the time (2) the frequency of both dyad members meeting individual weekly stepping goals was 81% compared to just one dyad member or no dyad member reaching the weekly step goal. This project revealed barriers using wearable sensor technology (i.e., not looking at or wearing the wearable sensor). Our discussion will focus on how to enhance meaningful interaction with technology in dyads to track daily stepping that can be applied to improve behavioral change in people with MCI and care partners.

Background: In Alzheimer’s disease and related disorders (ADRD) research, common outcome measures include cognitive and functional impairment, as well as persons with mild cognitive impairment (pwMCI) and care partner self-reported mood and quality of life. Studies commonly analyze these measures separately, which potentially leads to issues of multiple comparisons and/or multicollinearity among measures while ignoring the latent constructs they may be measuring. Objective: This study sought to examine the latent factor structure of a battery of 12-13 measures of domains mentioned above, used in a multicomponent behavioral intervention (The HABIT® program) for pwMCI and their partners. Methods: Exploratory factor analysis (EFA) involved 214 pwMCI-partner pairs. Subsequent Confirmatory factor analyses (CFA) used 730 pairs in both pre- and post-intervention conditions. Results: EFA generated a three-factor model. Factors could be characterized as partner adjustment (29.9%), pwMCI adjustment (18.1%), and pwMCI impairment (12.8%). The subsequent CFA confirmed our findings, and the goodness-of-fit for this model was adequate in both the pre- (CFI = 0.937; RMSEA = 0.057, p = 0.089) and post-intervention (CFI = 0.942; RMSEA = 0.051, p = 0.430) groups. Conclusion: Results demonstrated a stable factor structure across cohorts and intervention conditions suggesting that three broad factors may provide a straightforward and meaningful model to assess intervention outcome, at least during the MCI phase of ADRD.

There is currently limited and mixed evidence for the cognitive benefits of Computerized Cognitive Training (CCT) and yoga in persons with Mild Cognitive Impairment (pwMCI). The objective of this study was to investigate the benefit of computerized cognitive training (CCT) vs. physical (yoga) intervention on cognitive abilities. Participants in this study were part of the larger Mayo Clinic’s Healthy Action to Benefit Independence and Thinking (HABIT) program comparative effectiveness trial. The HABIT program is designed for pwMCI and their care partner and consists of five behavioral interventions: CCT, Memory Support System-Calendar (MSS-Calendar), wellness education, support groups, and yoga. The subtractive study design randomly withheld one of the interventions for a total of five study arms. Longitudinal mixed-effects regression models were used to investigate the hypothesis that CCT and yoga has a greater positive impact on psychomotor and basic attention abilities at 12 months post-intervention as compared to the other HABIT interventions. Findings showed CCT had a positive impact compared to yoga on the Cogstate psychomotor/attention composite at 12 months post-intervention (ES = 0.54; unadjusted p value = 0.007, adjusted p value = 0.021). The impact of yoga or combining CCT with yoga did not show statistically significant improvement. Continued CCT practice at home showed further benefit on psychomotor/attention at 12 months post-intervention. There was no significant benefit of CCT or yoga on Cogstate learning/working memory composite.

AbstractBackgroundThe American Academy of Neurology Practice Guidelines recommends physical exercise to help maintain cognition in people with Mild Cognitive Impairment (pwMCI). We previously demonstrated yoga’s benefit in maintenance of memory related activities of daily living at one year follow‐up in pwMCI (Chandler et al., 2019), and yoga may be beneficial in offsetting a sense of burden in care partners at 12 months (Amofa et al., submitted). In this analysis, we sought to examine the impact of yoga training on physical performance in pwMCI and their care partners.MethodIn this multisite, randomized clinical trial, we enrolled 272 patients meeting National Institute on Aging–Alzheimer’s Association criteria for MCI and a care partner. The intervention program was modeled on the 10 day Mayo Clinic HABIT Healthy Action to Benefit Independence and Thinking® program. Of 5 possible interventions (memory compensation training, computerized cognitive training, yoga, patient and partner support groups, and wellness education), 1 of 5 interventions was randomly selected to be withheld for each intervention group, thus allowing us to examine comparative effectiveness. Participants and their partners had 1‐day booster sessions at 6 and 12 months after intervention. The Short Physical Performance Battery (SPPB), a measure of balance, gait speed, and repeated chair stands was used to assess physical function outcomes.ResultThere was a general pattern of physical decline on the SPPB over the year in pwMCI, regardless of yoga training (d=‐0.04, p=0.78) (Figure 1, Panel A). Among care partners, those randomized to the no yoga group had a worse decline in physical function compared to those receiving yoga (d=‐0.31, p=0.034) (Figure 1, Panel B). While not reaching statistical significance in subgroup comparisons, yoga training tended to have a greater effect on SPPB than computerized cognitive training (d = 0.35, p = .06) or wellness education (d = 0.32, p =.09) (Table 1).ConclusionParticipation in yoga had a positive impact on physical performance outcomes at one year for care partners, but did not counteract general physical decline in pwMCI.

Background: Research has shown that individuals with mild cognitive impairment (MCI) value quality of life (QoL) above and beyond cognitive function or other potential outcomes in MCI. There is evidence supporting the negative impact of poor physical function on QoL ratings. Objective: The study explored whether a modified measure of self-efficacy for managing MCI and education mediated and/or moderated the relationship between physical function and QoL in persons with MCI. Methods: Baseline data from 200 participants with MCI were obtained from a larger study assessing the effectiveness of a behavioral intervention. Physical function was assessed by the Short Physical Performance Battery. QoL was assessed with the Quality of Life in Alzheimer’s Disease scale. Memory-related self-efficacy was assessed using a modified 9-item version of the Chronic Disease Self-Efficacy Scales. Mediation and moderation analyses tested the hypotheses that self-efficacy and education alter the association between physical function and QoL in individuals with MCI. All analyses were adjusted for age, cognitive severity, and sex. Results: Self-efficacy for managing MCI was a significant mediator of the association between physical function and perceived QoL. Individuals with better physical function reported higher self-efficacy which was associated with higher QoL ratings. Conclusions: Greater self-efficacy for managing MCI mediated the negative association between physical function and quality of life in this exploratory study. Interventions aimed at enhancing memory self-efficacy in MCI may improve perceived QoL, even in the presence of poor physical function. Future research is needed to investigate this further.