Symposia
Telehealth/m-Health
Adriana Hughes, Ph.D. (she/her/hers)
Staff Neuropsychologist
Minneapolis VAMC
Minneapolis, Minnesota
Destiny Weaver, B.S.
Research Assistant
Minneapolis VA Health Care System
Minneapolis, Minnesota
Anael Kuperwais Cohen, B.A.
Research Assistant
Minneapolis VA Health Care System
Minneapolis, Minnesota
Samuel Lee, B.S.
Research Assistant
Minneapolis VA Health Care System
Minneapolis, Minnesota
Catherine Ju, B.A.
Research Assistant
Minneapolis VA Health Care System
Minneapolis, Minnesota
Zachary Beattie, PhD
Assistant Professor
Oregon Health & Science Unviersity
Portland, Oregon
Yan Liu, MS
Researcher
Oregon Health & Sciences University
Portland, Oregon
Chao-Yi Wu, PhD, OT
Data Scientist
Massachusetts General Hospital
Boston, Massachusetts
Sarah Gothard, B.S.
Researcher
Oregon Health & Sciences University
Portland, Oregon
Hiroko Dodge, PhD
Associate Professor
Massachusetts General Hospital
Boston, Massachusetts
Alyssa De Vito, PhD
Postdoctoral Fellow
Brown University
Providence, Rhode Island
John Ferguson, Ph.D.
Associate Professor
University of Minnesota
Minneapolis, Minnesota
Background: Subtle functional cognition changes that emerge early during mild cognitive impairment (MCI) are challenging to detect with current assessment methods. Mobile and in-home sensor technologies may be able to alter the clinical care pathway by capturing changes in day-to-day functional cognition, thereby improving MCI early identification as well as being able to effectively monitor symptom progression and identify those who would benefit from additional support and/or a higher level of care. We examined the feasibility of mobile and in-home sensors for monitoring functional cognition in a longitudinal study of cognitively unimpaired (CU) and MCI older adults.
Methods: Clinical data were collected at baseline and annually for up to four years. Sensor-based functional cognition data were collected in medication pillbox use, driving activity, and computer use. Participants completed a brief weekly online health update survey and a brief monthly online cognitive measure.
Results: Participants were 104 older adults (Mage=74.7, 43% MCI, 62% male, 90% White, 57.7% Veterans, and Medu=15.6 years) with an average follow up of 956 (SD= 347) days. Driving activity was measured using a driving sensor for 60 participants for an average of 256 days, with 170 days on average with driving data, and then using a different driving sensor for 88 participants for an average of 468 days, with 319 days on average with driving data. Computer use was monitored for 72 participants for an average of 821 days, with participants using their computers for 495 days on average. A brief online cognitive measure was sent to 104 participants monthly for an average of 31 months, with the measure being completed on average for 30 months. A brief online health update survey was sent weekly to 104 participants for an average of 134 weeks, with the survey being completed for an average of 130 weeks. Adherence rates for completing the weekly survey were 95.6% for MCI and 98.6% for CU; and for the monthly cognitive measure: 93.7% for MCI and 98.8% for CU during the baseline period. Study retention was high; 14 participants (13%) withdrew over follow up; most commonly due to unanticipated medical events (29%).
Conclusion: Monitoring multiple domains of functional cognition was feasible and well-accepted in a longitudinal study of CU and MCI older adults. Future work will report on the validity and utility of the sensor-based functional cognition data. These technologies have the potential to improve MCI early detection and increase effectiveness of prevention and treatment.