PST has advantages over SDMT because of its efficient administration, scoring, and potential for medical record or research database integration. PST is a practical tool for routine screening of processing speed deficits in the MS clinic.
Advancements in body-worn activity devices make them valuable for objective physical activity measurement. Research-grade monitors utilize software algorithms developed with younger populations using waist-worn devices. ActiGraph offers the low frequency extension (LFE) filter which reduces the movement threshold to capture low acceleration activity that is more common in older adults. It is unclear how this filter changes activity variable calculations in older adults. We investigated the effects of the LFE filter on wrist-worn activity estimates in this population. Participants were 21 older adults who wore the GT9X on their non-dominant wrist for 7 days in a free-living environment. Activity counts were estimated both with and without the LFE filter. Paired samples t-tests revealed that the LFE estimated significantly higher number of counts than non-LFE calculated counts per minute on all three axes (p < .001). Step count estimates were higher with (M = 20,780.09, SD = 5300.85) vs. without (M = 10,896.54, SD = 3489.45) the LFE filter, (t (20) = -22.21, p < .001). These differences have implications for calculations based on axis counts (e.g., Axis-1 calculated steps, intensity level classifications) that rely on waist-worn standards. For example, even without the filter, the GT9X calculated an average of 10,897 steps, which is likely an overestimate in this population. This suggests that axes-based variables should be interpreted with caution when generated with wrist-worn data, and future studies should aim to develop separate wrist and waist-worn standard estimates of these variables in older adult populations.
Chronotype refers to the time of day that people prefer to be active or to sleep and varies predictably across the lifespan. In younger samples, the morning-chronotype is related to greater levels of physical activity (PA) and improved health outcomes. It is unclear whether this pattern holds in older adults, a group that commonly exhibits an “early bird” preference. We investigated differences in PA patterns between chronotypes in 109 older adults (Mage = 70.45 years) using wrist-worn ActiGraphs in a free-living environment. ActiGraphs captured data about PA and sleep using a novel approach to measuring chronotype with the mid-point of the sleep interval. We categorized participants as morning-, intermediate-, or evening-chronotypes. We used ANCOVA to predict total and average peak PA from chronotype, adjusting for age, sex, education, and BMI. Total PA significantly differed between chronotypes such that evening-types engaged in less PA than both morning- and intermediate-types, F (2,102) = 4.377, p =.015. Average peak activity did not differ between chronotypes, p =.112. Consistent with findings in younger samples, our evening type participants engaged in less overall activity. A unique finding was that evening-types did not differ from their morning- and intermediate-chronotype peers in peak activity levels. This implies a key distinction between total activity and peak activity levels consistent with recent trends in PA research using a 24-hour-a-day framework instead of average or total activity levels. Future research should consider whether these differences in activity patterns translate into meaningful differences in health benefits in this age group.
There are unique challenges to recruit and enroll individuals with Alzheimer’s disease (AD) into research studies, and typical barriers to participation include the need for study partner involvement, use of invasive procedures (e.g., lumbar punctures), and lack of awareness of ongoing research. Failure to enroll this population impacts generalizability and external validity of results. The current study sought to explore reasons for non-participation in individuals with AD enrolled in the University of Kansas Alzheimer’s Disease Center (ADC) Registry. Participants were approached at their annual registry visit and asked to participate in an observational sub-study that utilized wrist-worn actigraphy to measure physical activity and sleep over a one-week period. Of the thirty-six non-participation encounters that were recorded over a 2.5 year data collection period, 28% were never recruited due to appointment cancellation, rescheduling, or no-show. Of the remaining encounters, the three most common reasons for non-participation included: physical limitations of individuals with AD (15%), unknown (28%), and study partner concerns regarding use of technology in individuals with impaired cognition due to AD (25%). Multiple study partners were concerned that the individual with AD would lose the watch, remove the watch from the wrist, or become irritated while wearing it. Findings suggest that the use of technology such as actigraphy presents an additional barrier to enrollment that is unique to individuals with AD. Future studies should consider potential interventions to address study partner concerns regarding use of technology in individuals with AD.
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