This report describes a pilot study to evaluate feasibility of new home-based assessment technologies applicable to clinical trials for prevention of cognitive loss and Alzheimer disease. Methods: Community-dwelling nondemented individuals ≥75 years old were recruited and randomized to 1 of 3 assessment methodologies: (1) mail-in questionnaire/ live telephone interviews (MIP); (2) automated telephone with interactive voice recognition (IVR); and (3) internet-based computer Kiosk (KIO). Brief versions of cognitive and noncognitive outcomes were adapted to the different methodologies and administered at baseline and 1-month. An Efficiency measure, consisting of direct staff-to-participant time required to complete assessments, was also compared across arms. Results: Forty-eight out of 60 screened participants were randomized. The dropout rate across arms from randomization through 1-month was different: 33% for KIO, 25% for IVR, and 0% for MIP (Fisher Exact Test P=0.04). Nearly all participants who completed baseline also completed 1-month assessment (38 out of 39). The 1-way ANOVA across arms for total staff-to-participant direct contact time (ie, training, baseline, and 1-month) was significant: F (2,33)=4.588; P=0.017, with lowest overall direct time in minutes for IVR (Mn=44.4; SD=21.5), followed by MIP (Mn=74.9; SD=29.9), followed by KIO (Mn=129.4; SD=117.0). Conclusions: In this sample of older individuals, a higher dropout rate occurred in those assigned to the high-technology assessment techniques; however, once participants had completed baseline in all 3 arms, they continued participation through 1 month. High-technology home-based assessment methods, which do not require live testers, began to emerge as more time-efficient over the brief time of this pilot, despite initial time-intensive participant training.
*Mount Sinai School of Medicine
‡NYU School of Medicine, New York
†The James J Peters VAMC, Bronx
§Nathan Kline Institute, Orangeburg, NY
∥Oregon Health & Science University, Portland, OR
¶Healthcare Technology Systems, Madison, WI
♯UCSD, La Jolla, CA
Reprints: Mary Sano, PhD, Mount Sinai School of Medicine, New York, NY (e-mail: firstname.lastname@example.org).
Received for publication April 5, 2009; accepted July 29, 2009
Supported by these NIA grants: U01AG10483, P50AG005138, P30AG008051, and P30AG024978. Development of the Kiosk and MedTracker was supported in part by grants from NIA (P30-AG024978; P30-AG08017) and Intel Corporation.