Principal Investigator: Wendy. A. Rogers, Ph.D.
Project Team: Katharina Echt, Ph.D., Brad Fain, Ph.D.; Brian Jones, Tracy. L. Mitzner, Ph.D.; Jenny Singleton, Ph.D.
Adults with disabilities are living longer and thus likely to experience age-related declines that can negatively influence their independence and quality of life. Common abilities that decline with age are sensory (e.g., vision, hearing, tactile), physical (e.g., strength; dexterity), mobility (e.g., balance; coordination), and cognitive]. However, there is little information about how normative age-related changes impact individuals who are already dealing with existing disability. The overarching goal of this project is to provide a need-based scientific foundation that is necessary for effective technology integration into the lives of older adults with disabilities.
Specific aims of this project are to:
1) provide the evidence for a taxonomy of everyday support needs;
2) assess user needs for home-based activities; and
3) create an integrated dataset to predict task performance and technology needs.
Aim 1: Taxonomy of Everyday Support Needs
RQ1. What is the frequency, nature, and distribution of problems with task performance in everyday activities and AT use faced by adults with hearing, vision, or mobility disability who experience additional age-related declines in sensation, perception, and motor control?
RQ2. What are current strategies for dealing with problems in task performance?
RQ3. How can the selection, optimization, compensation (SOC) model be extended to distinguish between elective- and loss-based selections that provide the basis of a taxonomy of everyday support needs?
Aim 2: Assess User Needs for Home-Based Activities
RQ1. What is the relationship between gait and balance and in-home mobility, performance of activities in the home (e.g., range, frequency, and nature of activity problems), and use/usability of AT devices and how does this change over time?
RQ2. What is the range, frequency, and nature of issues associated with medication adherence? Which strategies or technological solutions are associated with higher rates of adherence for specific combinations of primary disability and secondary functional loss?
Aim 3: Integrated RERC Dataset to Predict Task Performance and Technology Needs
RQ1. What is the impact of functional ability (e.g., gait speed, accuracy, balance) and personal factors (e.g., age, demographics) on activity performance (e.g., task completion, difficulty, independence)?
RQ2. What are the salient functional performance factors that are associated with activity performance within and across activities?
RQ3. What patterns of functional performance and demographics predict task performance across activities?