Multicontext Approach for Cognitive Function in Parkinson Disease

The Multicontext Approach is a strategy training approach to cognitive intervention provides ways to maintain daily function despite the presence of cognitive deficits. It involves teaching people to use metacognitive, compensatory, or adaptive techniques to optimize information processing or bypass cognitive limitations and achieve task-related goals. Strategy training is recommended for those with mild (vs. more severe) cognitive deficits because it requires learning, capitalizes on existing cognitive resources, and aims to prevent or delay functional decline.

This treatment is functional task training, a widely-used approach in neurorehabilitation153,154 that parallels the cognitive training used in PD to-date but with functional cognitive tasks (vs. computer or paper \& pencil tasks) to improve ecological validity. It has the same structure within and across treatment sessions and uses the same treatment activities as the MC intervention. However, the OT does not use mediated learning techniques or explicitly address strategies, metacognition, or transfer/generalization. Rather, participants practice functional cognitive tasks with knowledge of results feedback and cueing by the OT to improve task performance.

MC+B participants will come from the MC Approach group only. They will receive 2 additional treatment sessions with their original OT within the month following their 6mo FU assessment. The OT will review the participant's relevant Post and FU data beforehand for treatment planning purposes. The first session will involve a review of goals, prior learning, and strategies and discussion of successes/challenges related to functional cognitive performance and strategy application since initial treatment. Then the same protocol (treatment activities with metacognitive framework and mediation, strategy bridging discussions, homework action planning and review) will be followed for the rest of the booster treatment to reinforce or re-activate prior learning, address new concerns, and develop supports for maintenance.