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Updated: May 20, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Implementation of a community-based mature driver screening and referral program: A feasibility study
Lea Ann Fortin-McCue1, Hassan Saleheen, Jacqueline McQuay
1The Trauma Institute, Hartford Hospital/Connecticut Children's Medical Center, 80 Seymour Street, Hartford, CT 06106, USA. lfortin@ccmckids.org
Abstract:
We tested the feasibility of implementing a community mature driver screening and referral program utilizing the Roadwise Review screening instrument. We recruited a convenience sample of 151 mature drivers (age 65 and over) at six community senior centers in suburban Connecticut. A 30 item survey collected demographic information, driving history, and self-reported vision, physical fitness, and attention problems. Participants completed a 30min computer screening program that assessed 8 areas associated with driving ability. Referrals were provided to participants with identified impairments. A post survey measured program satisfaction; a two week follow-up determined intent to address impairments. Among the problems/issues reported: reading highway/street signs or seeing other vehicles at night (25%), trouble looking over shoulder when changing lanes (18%), avoidance of night driving (22%) or in unfamiliar places (31%). Screening found mild impairments in 86% of participants and 52% with serious impairments. Referrals were given to 75%; at follow-up, 74% reported intent to complete referrals. Most participants (94%) would recommend the program to family/friends. In conclusion, this study was feasible to implement and identified driving impairments among mature drivers. Most participants intended follow-up with driving recommendations and program satisfaction was high.

