23 research outputs found
Human-first, please: Assessing citizen views and industrial ambition for emotional AI in recommender systems
OBJECTIVELY MEASURED SLEEP CHARACTERISTICS OF OLDER ADULTS WITH AND WITHOUT ALZHEIMER’S DISEASE
This is a pre-copyedited, author-produced version of an article accepted for publication in Innovation in Aging following peer review. The version of record Laffer, A., Hicks, H. J., Losinski, G., & Watts, A. (2019). OBJECTIVELY MEASURED SLEEP CHARACTERISTICS OF OLDER ADULTS WITH AND WITHOUT ALZHEIMER’S DISEASE. Innovation in Aging, 3(Suppl 1), S1–S2. https://doi.org/10.1093/geroni/igz038.002 is available online at: https://doi.org/10.1093/geroni/igz038.002.
This work is licensed under a Creative Commons Attribution 4.0 International License.Older adults commonly experience disturbed sleep such as difficulty initiating or maintaining sleep. Older adults who experience impaired sleep are at increased risk for cognitive decline or developing Alzheimer’s disease (AD). Research has shown that people with AD experience changes in sleep patterns, however, these changes are not well characterized. To better understand sleep in an older adult population with and without AD, the present study aimed to describe and compare objective sleep characteristics in both. Participants were older adults (126 with and 41 without AD) who wore an ActiGraph GT9X monitor on their non-dominant wrist for 7 days in a free-living environment. Results suggest that, compared to those without AD, participants with AD spent significantly more time in bed, t (165) = -4.37, p = .001), slept for longer durations, t (165) = -2.39, p = .044), and had less efficient sleep, t (165) = 2.71, p = .007. Participants with AD also had significantly greater sleep onset latency, more time awake after sleep onset, longer awakening lengths, and tended to arise later in the morning (all p ≤ .016). No differences were found between the groups in age, bedtime, or the number of awakenings during the night. These findings add to our understanding of the sleep disturbances experienced by older adults with and without AD. Significant group differences suggest that interventions may be necessary in treating sleep disturbances for older adults with and without AD. Future studies should examine sleep longitudinally to understand risk factors related to AD
ACTIGRAPH’S LOW-FREQUENCY EXTENSION FILTER FOR ESTIMATING WRIST-WORN PHYSICAL ACTIVITY IN OLDER ADULTS
This is a pre-copyedited, author-produced version of an article accepted for publication in Innovation in Aging following peer review. The version of record Hicks, Hilary J et al. “ACTIGRAPH’S LOW-FREQUENCY EXTENSION FILTER FOR ESTIMATING WRIST-WORN PHYSICAL ACTIVITY IN OLDER ADULTS.” Innovation in Aging vol. 3,Suppl 1 S520–S521. 8 Nov. 2019, doi:10.1093/geroni/igz038.1918 is available online at: https://doi.org/10.1093/geroni/igz038.1918.
This work is licensed under a Creative Commons Attribution 4.0 International License.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
EXAMINING SEX DIFFERENCES WITHIN THE RELATIONSHIP BETWEEN PHYSICAL ACTIVITY AND EXECUTIVE FUNCTION IN OLDER ADULTS
This is a pre-copyedited, author-produced version of an article accepted for publication in Innovation in Aging following peer review. The version of record Losinski, G., Hicks, H. J., Laffer, A., & Watts, A. (2019). EXAMINING SEX DIFFERENCES WITHIN THE RELATIONSHIP BETWEEN PHYSICAL ACTIVITY AND EXECUTIVE FUNCTION IN OLDER ADULTS. Innovation in Aging, 3(Suppl 1), S519–S520. https://doi.org/10.1093/geroni/igz038.1915 is available online at: https://doi.org/10.1093/geroni/igz038.1915.
This work is licensed under a Creative Commons Attribution 4.0 International License.Research has demonstrated sex-associated differences in physical activity and its benefits on cognition in older adults. The present study explored differential associations between moderate-to-vigorous physical activity (MVPA) and executive function, which is known to decline with aging. N = 53 older adults without cognitive impairment (M = 73.19 years, SD = 6.53) wore accelerometers (Actigraph GT3X+) during 7 consecutive days. Activity intensity was categorized as light, moderate, or vigorous based on Freedson Adult Vector Magnitude cutpoints. Participants completed a battery of executive function tests: Digit Symbol Substitution Test, Verbal Fluency, Trail Making Test, and Stroop Color-Word Test. A cognitive composite score was created using confirmatory factor analysis. Women had a higher mean MVPA (4.57%) than men (2.64%, t (19.04) = -2.49, p = .022). However, executive function performance did not differ by sex (t (26.20) = 1.67, p =.107). The interaction between sex and time in MVPA did not predict performance on executive function, adjusting for age and education. Older age was the only significant predictor of poorer executive function (β = -0.038, p = .003). The current sample had limited engagement in MVPA (range 0.18-10.87%). These findings suggest that the amount of engagement in MVPA in a free-living environment may not be sufficient to demonstrate sex-associated differences in executive function performance. Future studies should explore executive function performance with other intensity levels and examine other areas of cognition
Using Actigraphy to Assess Chronotype and Physical Activity in Older Adults
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
THE EFFECT OF ACTIGRAPHY MEASURED PHYSICAL ACTIVITY ON EXECUTIVE FUNCTION IN OLDER ADULTS
Executive function (i.e., decision making, self-control, planning) is important for facilitating independent living in older adults. Physical activity may preserve executive function, but previous research has demonstrated sex differences in both physical activity and executive function among older adults. Few studies have investigated sex differences in the association between the two. We examined associations between objectively measured physical activity and executive function with attention to sex differences. We recruited N = 204 participants (Mage =71, SD=6.36; 57% women) with (n=47) and without (n=157) Alzheimer’s disease from the University of Kansas Alzheimer’s Disease Research Center. We used wrist-worn accelerometers (Actigraph GT9X) to measure physical activity 24 hours a day for 7 days in a free-living environment. We categorized physical activity as moderate to vigorous (MVPA) based on the Montoye (2020) Adult Vector Magnitude cut-points. We evaluated sex differences in the association between executive function and MVPA using multiple regression with an interaction term, adjusting for age, education, and dementia status. We used a composite score to combine tests of executive function (Digit Symbol Substitution, Stroop Interference, Trail making Part B, and Verbal Fluency). Results indicated, older age and lower education were associated with lower executive function scores (β=-2.12, p < 0.001; B=2.13, p < .05). In contrast to previous research, we did not find evidence for sex differences in the MVPA, executive function, nor the association between the two in our sample. Future research should investigate whether individualized exercise-based interventions and treatment between men and women may differentially benefit cognitive function
Attitudes Towards Emotional Artificial Intelligence Use: Transcripts of Citizen Workshops Collected Using an Innovative Narrative Approach, 2021
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