Morris Bell - US grants

DESCRIPTION (Adapted from the Applicant's Abstract): This study proposes to enroll 120 men and women with schizophrenia or schizoaffective disorder in a five-year investigation to compare work therapy alone with work therapy augmented by cognitive enhancement training. The cognitive enhancement condition has 4 elements: a) feedback to patients about their cognitive strengths and weaknesses from the baseline cognitive assessment; 2) 150 sessions of cognitive retraining employing computer-based hierarchically arranged exercises for memory, attention, and executive function; 3) a weekly group to improve verbal expression and social information processing; and 4) cognitively oriented work performance feedback in a weekly group with goal-setting and problem-solving. The work only condition will include 2 non-cognitive groups to control for non-specific effects. The work therapy program for both conditions will provide paid work activity ($6.00/hr.) for up to 20 hours per week in an accommodating setting with appropriate work service supports. Randomization into condition will be stratified by baseline cognitive functioning. Subjects will be provided with 12 months of work plus the procedures of their randomized condition. They will then be allowed to continue with work services for an additional 12 months. Clinical quality of life, neuropsychological, and rehabilitation effects will be assessed at 1- and 2-year follow-up. The two primary aims are 1) to determine whether cognitive enhancement training improves functional outcomes for this population and whether cognitive enhancement is especially needed to maintain work functioning for subjects with severe cognitive impairment; and 2) to determine whether paid work activity, which has demonstrated efficacy in veteran samples, is effective for a community sample of men and women. Two secondary aims are 1) to determine whether there are significant gender differences in the predictors, process and outcome of cognitive enhancement and work therapy; and 2) whether the provision of these services is cost effective from the point of view of the provider, the consumer and family, and society.

DESCRIPTION (provided by applicant): The Department of Psychiatry at Yale University School of Medicine requests the first renewal of a 5 year post-doctoral research training grant for intervention and services research in treatment, rehabilitation, and prevention of severe mental disorders. This grant provides support for a total of 2 physicians and 2 Ph.D. psychologists per year. Post-doctoral trainees spend two to three years at Yale to obtain clinical and research training while being mentored by faculty investigators whose interests include neuroscience, cognitive and vocational rehabilitation, early intervention, epidemiology and health services research. Our multi-disciplinary program enables trainees to engage in research from trials on promising new approaches to effectiveness studies in health systems. The main purpose of this proposal is to provide post-doctoral trainees the opportunity to devote full-time effort to learning the skills needed to become independent researchers and clinician scientists. Prospective trainees identify a faculty mentor and develop a proposed training plan as part of the application procedure. During the training program, trainees participate in seminars and courses on health services research, neuroscience, biostatistics, research design, translational research and responsible conduct of scientific research. They participate in a mentored rotation on the IRB. Direct involvement in community settings, stimulation of cutting-edge neuroscience, exposure to systems issues at a state, national, and international level, and intensive training in research methods provide a rich experience that encourages trainees to generate original research. Projects have included such topics as early detection of psychosis, the recovery process, changing patterns of child psychiatric services, mental health services for the deaf and hearing impaired, cognitive remediation in substance abuse treatment, and fMRI assessment of cognitive retraining in schizophrenia. Under faculty mentors, trainees gain experience in clinical research, from initial conceptualization and design, through implementation, data analysis and manuscript preparation. Four fellows have completed their training and four are currently in training. Graduates have continued their independent research as faculty at leading medical centers.

[unreadable] DESCRIPTION (provided by applicant): Cognitive deficits are a prominent and disabling feature of schizophrenia that persist despite optimal pharmacotherapy. Repeated studies show links between these deficits and functional outcomes. Thus, there is a great need for new treatments for cognitive deficits. Our preliminary VA studies have demonstrated that patients improved on computer-based cognitive training tasks (CCT), that improvements generalized to neuropsychological test improvements and that CCT led to changes in brain activation. Additionally, CCT plus cognitively-oriented rehabilitation methods yielded superior outcomes in our VA work therapy program including more hours worked and more dollars earned at follow-up. Results of our current NIMH funded study of CCT plus cognitively oriented rehabilitation methods show better vocational outcomes in community-based supported employment (SE) including better work performance, more hours worked and higher employment rates at 2-yr FU. In this submission for a competitive renewal we propose to isolate the contribution of CCT by comparing CCT + Enhanced SE to Enhanced SE alone to determine whether CCT is necessary for producing favorable outcomes. We will enroll 100 people with schizophrenia or schizoaffective disorder at 2 Connecticut CMHCs and randomly assign them to condition. CCT will involve intensive computer-based hierarchical training on attention, memory, and executive function tasks for up to10 hrs/wk for up to 1 yr. SE will be based on the Individual Place and Support model (IPS). Enhancements include the use of transitional funds for rapid placement, a weekly work performance feedback group, and a social information processing group. Assessment at baseline, 1 yr. FU, and 2 yr. FU will focus on cognitive and vocational outcomes, but will also include clinical status, quality of life and community function measures. Predictors of response to training will also be examined. [unreadable] [unreadable]

DESCRIPTION (provided by applicant): This proposal aims to pilot test a cognitive remediation therapy (CRT) combined with work therapy (WT) as an adjunct to the initial phase of outpatient substance abuse treatment. There is ample research evidence of cognitive impairment across substance abuse disorders, particularly in the early phase of recovery. Cognitive impairment has been associated with poorer substance abuse treatment outcomes and may be remediated through programs of exercises that target these impairments. We have previously reported on a model of providing CRT with work therapy (WT) in an outpatient context for people with psychotic disorders, which showed significant improvements in executive function and working memory, and in important functional outcomes such as work performance and sustained work activity. We propose to apply this same approach to a sample of participants recruited from a 30-day residential program for substance abusers who are beginning their recovery. When they are discharged, they will be able to continue WT, which may encourage their engagement in CRT and in substance abuse outpatient services. Our Specific Aims are: 1. Test the feasibility and tolerability of CRT &WT in the early phase of substance abuse treatment. 2. Obtain effect size for CRT &WT compared to WT alone on a primary substance abuse outcome measure (Percent Days of Abstinence, PDA) for a future R01 RCT submission. 3. Obtain effect sizes for secondary outcomes (cognitive, psychosocial, vocational). 3. Examine effects of moderators such as age, type of substance abuse, and cognitive functioning that may be relevant for determining inclusion/exclusion criteria for an RCT. 4. Examine mediators of outcome such as neuropsychological change and treatment adherence to understand the mechanisms of treatment effects. We propose to accomplish these aims by randomizing 50 participants who wish to receive WT services into two conditions: 25 will be assigned to 15 hours of WT plus 5 hours of CRT each week (CRT+WT) and 25 will be assigned to an active control of 20 hours of WT. The active intervention will be for 13 weeks. CRT will be comprised of a repetitive training on a hierarchy of progressive visual and auditory exercise from Posit science. WT will involve paid work activity in a placement of their choosing on the medical center campus. Participants will be paid the same hourly rate (half federal minimum wage) for their time in CRT and WT. Comprehensive assessments will be performed at intake, 3 months and 6 months. These will include substance abuse, cognitive, and psychosocial outcomes as well as adherence to treatment. During the 3 months of active intervention participants will have weekly observed urine toxicology screens, breathalyzer tests and PDA assessments, as well as monthly work performance evaluations. Data analyses will include random effects regression models, as well as models of moderator and mediator effects on the primary outcome of PDA. If meaningful effects are found, these results will guide a subsequent R01 submission. PUBLIC HEALTH RELEVANCE: This study will pilot test the use of cognitive remediation therapy combined with work therapy to learn whether outpatients with primary substance use disorders will engage in this treatment and whether it will lead to better cognitive and substance abuse outcomes than having work therapy without cognitive remediation. Findings may offer guidance for further testing a new model of treatment that may engage outpatients more effectively and lead to more rapid recovery.

The identification of cognitive impairments in early childhood provides the best opportunity for successful remedial intervention, because brain plasticity diminishes with age. Attention deficit hyperactivity disorder (ADHD) is a psychiatric neurodevelopmental disorder that is very hard to diagnose or tell apart from other disorders. Symptoms include inattention, hyperactivity, or acting impulsively, all of which often result in poor performance in school and persist later in life. In this project, an interdisciplinary team of computer and neurocognitive scientists will develop and implement transformative computational approaches to evaluate the cognitive profiles of young children and to address these issues. The project will take advantage of both physical and computer based exercises already in place in 300 schools in the United States and involving thousands of children, many of whom have been diagnosed with ADHD or other learning disabilities. Project outcomes will have important implications for a child's success in school, self-image, and future employment and community functioning. The PIs will discover new knowledge about the role of physical exercise in cognitive training, including correlations between individual metrics and degree of improvement over time. They will identify important new metrics and correlations currently unknown to cognitive scientists, which will have broad impact on other application domains as well. And the PIs will develop an interdisciplinary course on computational cognitive science and one on user interfaces for neurocognitive experts.

The research will involve four thrusts. The PIs will devise new human motion analysis and computer vision algorithms that can automatically assess embodied cognition during structured physical activities, and which will constitute a breakthrough in improving the accuracy and efficiency of cognitive assessments of young children. Intelligent mining techniques will be used to discover new knowledge about the role of physical exercise in cognitive training and to find correlations between individual metrics and degree of improvement over time. A methodology will be developed using advanced multimodal sensing to collect and process huge amounts of evidence based assessment data with intelligent mechanisms that learn about a child's executive function capabilities and help uncover possible causes of cognitive dysfunctions. And a closed loop cognitive assessment system will be designed and implemented to understand and monitor a child's progress over time and provide recommendations and decision support to cognitive experts so they can make better treatment decisions.

Automation, foreign competition, and the increasing use of robots replacing human jobs, stress the need for a major shift in vocational training practices to training for intelligent manufacturing environments, so-called "Industry 4.0". In particular, vocational safety training using the latest robot and other technologies is imperative, as thousands of workers lose their job or die on the job each year due to accidents, unforeseen injuries, and lack of appropriate assessment and training. The objective of this Partnerships for Innovation: Building Innovation Capacity (PFI:BIC) project is to develop iWork, a smart robot-based vocational assessment and intervention system to assess the physical, cognitive and collaboration skills of an industry worker while he/she performs a manufacturing tasks in a simulated industry setting and collaborating with a robot to do the task. The aim is to transform traditional vocational training and rehabilitation practices to an evidence-based and personalized system that can be used to (re)train, retain, and prepare workers for robotic factories of the future. The need for personalized vocational training, rehabilitation and accurate job-matching is essential to ensuring a strong manufacturing sector, vital to America's economic development and ability to innovate. The iWork service is "smart" because it can adjust and adapt to the individual's abilities as it assesses him/her and help decide on the type of tasks needed to test and train, based on the job's complexity, difficulty or familiarity to the worker. The iWork system integrates human expert knowledge to overcome or compensate for detected worker constraints.
Research has shown that robot trainers can increase motivation and sustain interest, increase compliance and learning, and provide training for specific and individual needs. The iWork system aims to assess and train both the human and the work-assistive robot, as they collaborate on a manufacturing job. The projected outcome is low-cost vocational training solutions that can have substantial economic and societal benefits to diverse economic sectors. Most importantly, if successful, projected outcomes could impact how millions of persons seeking a manufacturing job are trained, including those facing a type of learning, physical or aging disability. The system's mobile, low cost methods accelerate recognizing a worker's specific needs and improve the ability of the vocational expert to make correlations between cognitive and physical assessments, thus empowering traditional practices with user-centric targeted training methods. In addition, the project's robot-based emphasis on safety and risk assessment, can reduce liability costs and productivity setbacks faced by industry, due to manufacturing accidents.
The iWork system uses computational methods in reinforcement (machine) learning, data mining, collaborative filtering and human robot interaction to collect and analyze multi-sensing worker data during a manufacturing human-robot collaboration simulation. Data collected and analyzed come from sensors, wearables, and explicit user feedback measuring worker movements, eye gazes, errors made, performance delays, human-robot interactions, physiological metrics, and others, depending on the task. The system has a closed loop architecture composed of four phases: assessment, recommendation, intervention (or adjustment), and evaluation, with a human expert in the loop. The system generates recommendations for personalized interventions to the expert, at different loop intervals. Use of the latest developments in sensing technologies, robotics and intelligent communications, assess the ability to enhance the intelligence of a robot co-worker with more human-like learning and collaboration abilities to support the human in achieving a task. The system is modular and customizable to a particular manufacturing task, domain or worker robot. Two types of robots are used, socially assistive robots that provide non-contact user assistance through feedback and physically assistive robots that provide cognitive, physical and collaboration skill training. To predict risks of injury due to inattention, age, vision, or physical and mental issues, motion analysis and kinematics experiments are conducted to determine the type of safety training needed, to assess how well a human interacts with a collaborative robot, and how best to train the robot to help the human overcome identified physical and other deficiencies in performing a given task. The project integrates three main areas of expertise, engineered service system design, where assistive robots interact with and train each other to collaborate; computing, sensing, and information technologies, where machine learning, data mining and recommender algorithms are used to identify behavioral patterns of interest, and recommend targeted interventions; and human factors and cognitive engineering that deploy methods from the team's expertise in workplace assessment, personalized psychiatric intervention, and evaluation methods of vocational satisfaction, work habits, work quality, etc., as they relate to job preparation and retention.
The project has an interdisciplinary team of experts from two collaborating universities, University of Texas Arlington (UTA) and Yale University, representing several fields, including human factors, psychology, computing, and industrial organization. The project deploys two primary industry partners, SoftBank Robotics (San Francisco, CA) manufacturer of humanoid service robots, and InteraXon (Canada), producing mobile EEG devices, who provides hardware, software and know-how to enhance iWork's functionality in cognitive activity monitoring. The broader context partners include, C8Sciences (USA), Assistive Technology Resources (USA), Barrett Technologies Inc. (USA), and the Dallas Veteran Affairs Research Corp. (USA).