AJOT CE: Activity Engagement and Everyday Technology Use Among Older Adults in an Urban Area
AJOT CE: Activity Engagement and Everyday Technology Use Among Older Adults in an Urban Area
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SKU: CEAJOT65

Publisher: AOTA Continuing Education

Published: 2018

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Product Overview

Earn CE Credit With AJOT Articles!

Learn about tested treatment strategies by reading AJOT articles in your area of practice. Become an evidence-based practitioner and demonstrate your knowledge by passing the course exam.  Articles have been selected for their relevance to practice, fresh ideas, and strong evidence supporting treatment and the distinct value of OT.

Credit: .1 CEUs (1.25 NBCOT PDU’s/1 contact hour)

Authors

Ryan Walsh, MA, is MSOT Student, Department of Occupational Therapy, University of Illinois at Chicago, Chicago, IL

Ruxandra Drasga, MBA, is MSOT Student, Department of Occupational Therapy, University of Illinois at Chicago, Chicago, IL.

Jenica Lee, OTD, OTR/L, is Clinical Assistant Professor, Department of Occupational Therapy, University of Illinois at Chicago, Chicago, IL.

Caniece Leggett, BS, is MSOT Student, Department of Occupational Therapy, University of Illinois at Chicago, Chicago, IL.

Holly Shapnick, MS, OTR/L, is OTD Student, University of Illinois at Chicago, Chicago, IL.

Anders Kottorp, PhD, OT Reg, is Professor and Dean, Faculty of Health and Society, Malmo University, Malmo, Sweden.

Abstract

OBJECTIVE. We investigated associations among activity engagement (AE), number of available and relevant everyday technologies, ability to use everyday technologies, and cognitive status among older adults in an urban area.

METHOD. This cross-sectional study included 110 participants and used three assessments: the Frenchay Activities Index to measure AE, the Everyday Technology Use Questionnaire to measure the number of and ability to use available and relevant everyday technologies, and the Montreal Cognitive Assessment to measure cognitive status. Data analyses used a one-way analysis of variance and a multiple linear regression model.

RESULTS. The number of available and relevant everyday technologies was significantly different (p <.001) among groups that varied in level of AE. Ability to use everyday technologies did not significantly differ among groups. Cognitive status did not explain level of AE when the number of available and relevant everyday technologies was considered.

CONCLUSION. Increasing the accessibility of available and relevant everyday technologies among older adults in an urban area may increase AE.

Learning Objectives

Following this course, the learner will be able to:

1.      List examples of everyday technologies that that older adults might use.

2.      Describe three specific measures (the Frenchay Activities Index, the Everyday Technology Use Questionnaire, and the Montreal Cognitive Assessment) that may be used in occupational therapy practice with older adults to assess cognition, activity engagement and everyday technology use.

3.      Discuss the association among activity engagement, availability and use of everyday technologies, and the cognitive status among urban older adults.

 

Exam questions for this course authored by Marie Morreale, OTR/L, CHT

 

Learning Level: Advanced

 

Target Audience: Occupational therapists and occupational therapy assistants

 

Content Focus: Category 1: Domain of OT; Category 2: OT Process: Intervention

 

Reference Information:

Walsh, R., Drasga, R., Lee, J., Leggett, C., Shapnick, H., & Kottorp, A. (2018). Activity engagement and everyday technology use among older adults in an urban area. American