A Facial Expression-based Personalization Engine (FPE) for Monitoring and Modulating Real-time Effective Engagement in Cognitive Training in Older Adults at Risk for AD/ADRD (CogT FACE Study Phase II)
试验速览
- 阶段
- 1 期
- 状态
- 招募中
- 入组人数
- 80
- 试验地点
- 1
- 主要终点
- multi-modal effective engagement index (AID)
研究概览
简要总结
How to ensure adherence to computerized cognitive training in unsupervised circumstances (e.g., at-home, self-administered) in older adults at risk for Alzheimer's disease (AD) or AD related dementia (AD/ADRD) is understudied. The objective of the R33 study is to test a novel facial expression-based personalization engine (FPE) for monitoring and modulating real-time effective engagement, with an ultimate goal of enhancing long-term adherence in unsupervised cognitive training in older adults at risk for AD/ADRD. Here, Effective engagement is defined as the extent to which someone is actively engaged and performing with significant attention and enjoyment while training, addressing a balance between adherence and cognitive gains/plasticity from the training. Based on previous work, the hypotheses include that (1) mental fatigue revealed in facial expressions will reflect a trainee's degree of effective engagement, which can be modified by modulating task novelty; (2) the proposed FPE will ensure the effective engagement in cognitive training by monitoring trainee facial expressions and modulating training in response, promoting the trainee's long-term adherence to the training and cognitive plasticity. A Stage II intervention efficacy study will be conducted to compare effective engagement and adherence in unsupervised cognitive training between training programs with vs. without FPE in older adults at risk for AD/ADRD. The proposed FPE may assist in monitoring and improving effective engagement and adherence in older adults with unsupervised cognitive training. In the current application, FPE in a cognitive training program called speed of processing training will be tested. However, such FPE may be embedded to any computerized cognitive training in future studies to help address adherence related issues.
研究设计
- 研究类型
- Interventional
- 分配方式
- Randomized
- 干预模型
- Parallel
- 主要目的
- Basic Science
- 盲法
- Double (Participant, Investigator)
入排标准
- 年龄范围
- 60 Years 至 89 Years（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •English speaking
- •Living in a home, or independent- or assisted-living facility
- •Adequate visual and hearing acuity
- •Anti-depressants, antipsychotics, and/or anxiolytics have been stable for at least 7 days
- •Memory medications have been stable for at least 3 months
- •Absence of neurological/vascular disorder (For neurological disorders with minor symptoms check with PI on case-by-case basis)
排除标准
- •be enrolled in another intervention study aimed at improving cognition
- •live in nursing home
- •diagnosed with Multiple Sclerosis, TBI, chronic heart failure, Parkinson's disease, dementia
研究组 & 干预措施
unsupervised cognitive training with personalized engine
total 6 week intervention
干预措施: Cognitive Remediation (Behavioral)
unsupervised cognitive training without personalized engine
干预措施: Cognitive Remediation II (Behavioral)
结局指标
主要结局
multi-modal effective engagement index (AID)
时间窗: up to 8 weeks, throughout the intervention sessions
facial expression+ECG
次要结局
- the time spent on training(up to 8 weeks, throughout the intervention sessions)
- self-report perceived fatigue(up to 8 weeks, throughout the intervention sessions)
- memory(baseline assessment at week 0, post-intervention assessment at week 7, followup assessment at week 13)
- executive function(baseline assessment at week 0, post-intervention assessment at week 7, followup assessment at week 13)
研究者
Feng Lin
Associate Professor
Stanford University