Patient-Centered Serious Games for Remote Cognitive Training in Older Adults with Mild Cognitive Impairment

以患者为中心的严肃游戏，用于对患有轻度认知障碍的老年人进行远程认知训练

• 批准号: 10190616
• 负责人: Jean Francois Daneault
• 金额: $ 43.68万
• 依托单位: UNIVERSITY OF MASSACHUSETTS AMHERST
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-04-15 至 2025-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10190616
• 关键词: Activities of Daily Living; Adopted; Algorithms; Area; Attention; Caregivers; Clinic; Clinical; Cognitive; Complement; Control Groups; Data; Data Set; Disease; Disease Management; Disease Progression; Elderly; Environment; Feedback; Frequencies; Future; Goals; Health; Health Technology; Health care facility; Health system; Healthcare; Home; Human; Impaired cognition; Individual; Industrialization; Informatics; Intervention; Investigation; Lead; Long-Term Care; Machine Learning; Measures; Outcome; Participant; Patient Education; Patients; Performance; Persons; Physical activity; Play; Protocols documentation; Randomized; Randomized Controlled Trials; Regimen; Rehabilitation therapy; Research; Research Personnel; Role; Self Administration; Short-Term Memory; Single-Blind Study; Symptoms; System; Tablets; Technology; Telephone; Therapeutic; Time; Training; Video Games; base; behavior change; caregiver education; chronic stroke; clinical investigation; clinical outcome measures; cognitive function; cognitive performance; cognitive training; community setting; compliance behavior; cost; design; digital; functional disability; group intervention; hemiparesis; improved; insight; interest; mHealth; mild cognitive impairment; normal aging; novel; patient engagement; patient oriented; personalized management; programs; prototype; psychological distress; recruit; rural area; selective attention; side effect; stroke survivor; tool; translational impact; treatment as usual; underserved area; usability

Project Summary/Abstract Mild Cognitive Impairment (MCI) is characterized by cognitive decline greater than expected from normal aging, which does not yet significantly interfere with the performance of activities of daily living. The therapeutic goal for MCI is to slow down the course of the disease progress and reduce the impact of clinical symptoms. There has also been a particular emphasis on non-pharmacological interventions because they can slow disease progression and are low cost, non-invasive, safe, and have no adverse side effects. Serious games have received great interests among researchers and clinicians as a promising, low-cost, non- pharmacological intervention tool that can help assess and train patients’ cognitive function in a variety of environments (e.g., in/outside the clinic). Serious games in healthcare represent digital applications focusing on educating, informing, and enhancing patients’ health by leveraging the entertainment components of video games. However, currently available solutions require substantial involvement of trained caregivers and clinicians to motivate patients to adhere to the intervention protocol, which acts as the key barrier to the widespread implementations of serious game-based interventions. To bridge these gaps, this project aims to develop a mobile-health (mHealth) technology designed to encourage the use of, and thereby maximizing the compliance to, serious game-based training in individuals with MCI outside the clinic. We plan to employ a tablet-based application – namely Neuro-World – composed of six serious games designed to stimulate working memory and selective attention, which is developed by our research team’s industrial partner. Fully leveraging the system’s ability to provide clinically meaningful insights related to patients’ cognitive performance from their gameplays, their progress over time, and their compliance behaviors (e.g., use frequency and duration), it is our ultimate research goal to develop an optimal, human-centered serious game platform that can motivate patients’ to better adhere to the technological regimen. To accomplish this research goal, Aim 1 will focus on evaluating the preliminary efficacy of our serious games as a training tool to improve cognitive function. We will perform a small single-blind randomized controlled trial in 50 individuals with MCI who will be randomized either to the intervention group or the control group. In Aim 2, we will develop machine learning-based algorithms to derive clinically meaningful information regarding cognitive function from the game performance. Aim 3 will finally investigate the optimal design of the mHealth system to maximize patients’ compliance with serious game-based training via human-centered design approaches. We believe that outcomes of this project will open a new door leading to previously unexplored datasets and understanding of patient-technology interactions to promote positive behavior changes to enable self- administered, serious game-based cognitive training, which can form the basis of a wide range of future investigations of hemiparesis rehabilitation and personalized disease management.

项目总结/文摘