SwePub - search: WFRF:(Drasga Ruxandra M.)

Enumeration	Reference	Cover	Find
1.	Walsh, Ryan J., et al. (author) Everyday Technology Use and Overall Needed Assistance to Function in the Home and Community Among Urban Older Adults 2020 In: Journal of Applied Gerontology. - : Sage Publications. - 0733-4648 .- 1552-4523. ; 39:10 Journal article (peer-reviewed)abstract Background: Older adults manage increasing numbers of everyday technologies to participate in home and community activities. Purpose: We investigated how assessing use of everyday technologies enhanced predictions of overall needed assistance among urban older adults. Method: We used a cross-sectional design to analyze responses from 114 participants completing the Everyday Technology Use Questionnaire, the Montreal Cognitive Assessment, and a sociodemographic questionnaire. We estimated overall needed assistance based on definitions in the Assessment of Motor and Process Skills. We created logistic regression models and receiver operator characteristic curves to analyze variables predicting overall needed assistance. Findings: With high specificity and sensitivity, the Everyday Technology Use Questionnaire and the Montreal Cognitive Assessment were the strongest predictors of overall needed assistance.

Walsh, Ryan J., et al. (author)
Everyday Technology Use and Overall Needed Assistance to Function in the Home and Community Among Urban Older Adults
2020
In: Journal of Applied Gerontology. - : Sage Publications. - 0733-4648 .- 1552-4523. ; 39:10
Journal article (peer-reviewed)abstract
- Background: Older adults manage increasing numbers of everyday technologies to participate in home and community activities. Purpose: We investigated how assessing use of everyday technologies enhanced predictions of overall needed assistance among urban older adults. Method: We used a cross-sectional design to analyze responses from 114 participants completing the Everyday Technology Use Questionnaire, the Montreal Cognitive Assessment, and a sociodemographic questionnaire. We estimated overall needed assistance based on definitions in the Assessment of Motor and Process Skills. We created logistic regression models and receiver operator characteristic curves to analyze variables predicting overall needed assistance. Findings: With high specificity and sensitivity, the Everyday Technology Use Questionnaire and the Montreal Cognitive Assessment were the strongest predictors of overall needed assistance.

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