Effects of attentional demand on input device use in younger and older adults

2003 ◽  
Author(s):  
Anne C. McLaughlin ◽  
Wendy A. Rogers ◽  
Arthur D. Fisk
Keyword(s):  
Older Adults ◽  
Input Device ◽  
Attentional Demand ◽  
Device Use

scholarly journals Mobile device use and the cognitive function and depressive symptoms of older adults living in residential care homes

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Lu Lin ◽  
Xiu-Chen Jing ◽  
Shu-Jiao Lv ◽  
Jing-Hong Liang ◽  
Li Tian ◽  
...  
Keyword(s):  
Older Adults ◽  
Depressive Symptoms ◽  
Cognitive Function ◽  
Residential Care ◽  
Mobile Device ◽  
Care Homes ◽  
Device Use

scholarly journals The Impact of Assistive Device Use on Disability and Depression Among Older Adults With Age-Related Vision Impairments

2006 ◽  
Vol 61 (5) ◽  
pp. S274-S280 ◽  
Author(s):  
A. Horowitz ◽  
M. Brennan ◽  
J. P. Reinhardt ◽  
T. MacMillan
Keyword(s):  
Older Adults ◽  
Assistive Device ◽  
Age Related ◽  
Device Use ◽  
The Impact

Functional Status and Adaptation: Measuring Activities of Daily Living and Device Use in the National Health and Aging Trends Study

2017 ◽  
Vol 30 (7) ◽  
pp. 1136-1155 ◽  
Author(s):  
Stephen Frochen ◽  
Shahla Mehdizadeh
Keyword(s):  
Older Adults ◽  
Activities Of Daily Living ◽  
Path Analysis ◽  
Functional Status ◽  
National Health ◽  
Daily Living ◽  
Living Arrangement ◽  
Disability Score ◽  
Older Americans ◽  
Device Use

Objective: The objective of this study is to evaluate the functional status and adaptation of older Americans and discover the factors that contribute to device use. Method: Using the community participants’ portion of the first round of National Health and Aging Trends Study (NHATS), we demonstrate the prevalence of device use and reduction in activities, creating a multilevel measure of activities of daily living (ADL) functionality as compared with Katz’s dichotomous measure. In determining whether adaptation is universal irrespective of age, sex, race, living arrangement, and income, or dependent on these variables, we create a measure of device use, performing a path analysis of the device use measure and sociodemographic variables, with disability score as an intervening measure. Results: ADL functionality becomes more nuanced between the Katz-ADL and NHATS-ADL. Age, sex, and living arrangement were predictors of device use; income was indirectly, whereas race was not. Discussion: When assessors design service plans, consideration should be given to older adults’ ability, capacity, and resources to adapt.

scholarly journals Mobile device use and the cognitive function and depressive symptoms of older adults living in residential care homes

2020 ◽  
Author(s):  
Lu Lin ◽  
Xiuchen Jing ◽  
Shujiao Lv ◽  
Jinghong Liang ◽  
Li Tian ◽  
...  
Keyword(s):  
Older Adults ◽  
Depressive Symptoms ◽  
Cognitive Function ◽  
Mobile Devices ◽  
Residential Care ◽  
Mobile Device ◽  
Care Homes ◽  
Device Use ◽  
The Impact ◽  
Moca Score

Abstract Background With the fast-paced aging and increasing digitalization of society, there has been a growing interest in the effect of mobile device use on cognitive function and depression in older adults. However, research examining this issue among older adults in residential care homes (RCHs) is scant. Therefore, this study aimed to examine the impact of mobile device use on the cognitive function and depressive symptoms of older adults living in RCHs. Methods A cross-sectional survey was conducted using a sociodemographic questionnaire, the Montreal Cognitive Assessment (MoCA) and the 15-item Geriatric Depression Scale (GDS-15). Results A total of 235 senior residents (aged 82.58 ± 5.54) in four RCHs were surveyed. Users of mobile devices had a significantly higher total MoCA score (25.02 ± 4.14) and a significantly lower GDS-15 score (3.28±2.74) than non-users (MoCA: 19.34 ± 5.21, GDS-15: 4.69±2.90). Multivariate linear regression indicate that mobile device use is significantly associated with total MoCA score, six of the seven sub-scores (visuospatial abilities and execution functions, attention, language, abstraction, delayed recall, and orientation)(P<0.05). Logistic regression showed that mobile device use was significantly associated with the level of depressive symptoms (OR=0.458, 95%CI=0.249-0.845). Conclusions Use of mobile devices has a significant association with the cognitive function and depressive symptoms of older adults living in RCHs, and thus should be encouraged as a measure to maintain and improve cognition and prevent depression.

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