Exercise Adherence and Virtual Reality Gaming for Older Adults at Risk for Falls

Grant Winner

Dean

Abstract

The phenomenon of interest is fall prevention exercise programs in older adults who live in the community. Evidence suggests that fall prevention exercise programs can help improve balance, thus reduce future falls and fall-related injuries. Despite successes of fall prevention exercise programs, fall rates and resulting injuries among older adults continue to rise. Older adults have difficulty adhering to exercise programs and prior research shows a gap in successfully integrating effective exercises into the daily activities of older adults.

Objective: This PFRDG project is a feasibility study to be conducted prior to a (future) pilot trial. The overall purpose of this research is to systematically investigate interventions that increase exercise adherence in older adults at risk for falls.

Methods: A feasibility study will be conducted using a prospective design with repeated measures to pilot the study procedures, and refine the interventions and measurement of variables. Data will be collected using performance tests of balance, surveys, accelerometer data, and daily dairies. The interventions are 13-week programs designed to test the feasibility of the exercise interventions, and include:

Virtual Reality-Exercise Group (Group-A): The virtual reality-exercise intervention incorporates physical movement challenges during the game, including strengthening, coordination, multi-tasking, hand-eye coordination, dynamic balance and core stability training. Participants will receive supervised in home virtual reality-exercise training sessions (i.e., 30-60 minutes in duration) by the PI, at weeks 1, 5, 9, and 13, alternating with telephone calls.

Virtual Reality-Exercise PLUS Online-Activity Group (Group-B): In addition to the virtual reality exercise intervention (described above), Group-B will incorporate a monthly online-activity with all members. The online-activity will allow for participants to play against human-controlled avatars (i.e., their fellow participants) in an online match.