Ph.D. University of Memphis, 1994
Office: Johnson Tower 312
Phone: (509) 335-0170
- Neuropsychology and Aging Laboratory
- Smart Environment Research
- Aging Assistive Technology Video Series
- Undergraduate Program in Gerontechnology Website
- Graduate Student Work – Lab TV Link
- Memory Notebook: CR-MFG Intervention and Manual: Please click to request a copy
- Instrumental Activities of Daily Living-Compensation (IADL-C) Questionnaire: Please click to request a copy
- Health Brain Aging Activity (HBAA) Questionnaire: Please click to request a copy
- Smart home
- Washington State Magazine – You Must Remember This
- Washington State Magazine – Helping people with memory loss
- Better Tests Needed to Pinpoint Memory Problems
- Computers help solve the challenges of aging
- Psychology 198: Honors Introductory Psychology
- Psychology 363: Psychology and Aging
- Psychology 490: Cognition and Aging
- Psychology 485/486: Gerontechnology 1 and 2
- Psychology 537: Clinic Assessment Practicum
- Psychology 575: Foundation of Neuropsychology
Dr. Schmitter-Edgecombe will be accepting a graduate student for Fall 2018 admissions.
Clinical and Cognitive Neuropsychology; Everyday Functioning; Memory and Executive Abilities; Rehabilitation; Smart and Assistive Technologies; Aging and Cognitively Impaired Populations (e.g., MCI, AD, PD and TBI).
Selected Recent Publications (see vita for full list):
*indicates graduate student
*Weakley, A., & Schmitter-Edgecombe, M. (in press). Naturalistic assessment of task interruption in individuals with mild cognitive impairment. Neuropsychology.
*Braley, R., Fritz, S., Van Son, C., & Schmitter-Edgecombe, M. (in press). Prompting Technology and Persons with Dementia: The Significance of Context and Communication. The Gerontologist. doi.org/10.1093/geront/gny071
*Alberdi, A. A., *Weakley, A., Schmitter-Edgecombe, M., Cook, D. J. Aztiria, A., Basarab, A., & Barrenechea, M. (in press). Smart homes predicting multi-domain symptoms related to Alzheimer’s disease. IEEE Journal of Biomedical and Health Informatics. DOI: 10.1109/JBHI.2018.2798062
*Sumida, C. A., *Vo, T., *Van Etten, E., & Schmitter-Edgecombe, M. (in press). Medication management performance and associated cognitive correlates in healthy older adults and older adults with aMCI. Archives of Clinical Neuropsychology. doi.org/10.1093/arclin/acy038
Schmitter-Edgecombe, M., Lamb, R., *McAlister, M., **Vo, T., & *Robertson, K. (in press). Development and psychometric properties of the Healthy Aging Activity Engagement Scale (HAAE). Aging and Mental Health. doi: 10.1080/13607863.2017.1414147
*Beaver, J. K., Wilson, K. & Schmitter-Edgecombe, M. (in press). Characterizing Omission Errors in Everyday Task Completion and Cognitive Correlates in Individuals with Mild Cognitive Impairment and Dementia. Neuropsychological Rehabilitation. DOI: 10.1080/09602011.2017.1337039
*Robertson, K., Schmitter-Edgecombe, M, Weeks, D & Pimental, J. (in press). Naturalistic assessment using a simulated environment: cognitive correlates and relationship to functional status in individuals with neurologic conditions. Archives of Clinical Neuropsychology. doi.org/10.1093/arclin/acx136
*Beaver, J. K., & Schmitter-Edgecombe, M. (2017). Multiple memory processes and everyday functional assessment in community-dwelling older adults. Archives of Clinical Neuropsychology, 32, 413-426. PMID: 27001974
*Fellows, R., *Dahmen, J., Cook, D., & Schmitter-Edgecombe, M. (2017). Multicomponent analysis of a novel digital trail making test. The Clinical Neuropsychologist, 31, 154-167. PMCID: PMC5286906, DOI: 10.1080/13854046.2016.1238510
*Tam, J., Von San, C., & Dyck, D., & Schmitter-Edgecombe, M. (2017). An educational video series to increase Aging Services Technologies awareness among older adults. Patient Education and Counseling, 100, 1564-1571. DOI: 10.1016/j.pec.2017.03.020
*McAlister, C., & Schmitter-Edgecombe, M. (2016). Content and temporal order memory for performed activities in Parkinson’s disease. Archives of Clinical Neuropsychology, 31, 700-709.
*Simon, C. M., & Schmitter-Edgecombe, M. (2016). The role of cognitive reserve and memory self-efficacy on compensatory strategy use: a structural equation approach. Journal of Clinical and Experimental Neuropsychology, 38, 685-699. DOI: 10.1080/13803395.2016.1150426
*McAlister, C., & Schmitter-Edgecombe, M. (2016). Everyday functioning and cognitive correlates in healthy older adults with subjective cognitive concerns. The Clinical Neuropsychologist, 30, 1087-1103. PMID: 27240886
*McAlister, C., & Schmitter-Edgecombe, M. (2016). Executive function subcomponents and their relations to everyday functioning in healthy older adults. Journal of Clinical and Experimental Neuropsychology, 38, 925-940. PMID 27206842
*Dawadi, P. N., Cook, D. J., & Schmitter-Edgecombe, M. (2016). Automated clinical assessment from smart-home based behavior data. IEEE Journal of Biomedical and Health Informatics, 20, 1188-1194. PMID: 2629348; DOI: 10.1109/JBHI.2015.2445754
*McAlister, C., Schmitter-Edgecombe, M., & Lamb, R. (2016). Examination of variables that may affect the relationship between cognition and functional status in individuals with mild cognitive impairment: a meta-analysis. Archives of Clinical Neuropsychology, 31, 123-147. PMID 27001974
*Weakley, A., *Williams, J., Schmitter-Edgecombe, M., & Cook, D. (2015). Neuropsychological test selection for cognitive impairment classification: a machine learning approach. Journal of Clinical and Experimental Neuropsychology, 37, 899-916. DOI: 10.1080/13803395.2015.1067290
Schmitter-Edgecombe, M., & *Robertson, K. (2015). Recovery of visual search following moderate to severe traumatic brain injury. Journal of Clinical and Experimental Neuropsychology, 37, 162-177. PMID: 25671675; DOI: 10.1080/13803395.2014.998170
*Sanders, C., *Low, C., & Schmitter-Edgecombe, M. (2014). Assessment of planning abilities in individuals with mild cognitive impairment using and open-ended problem-solving task. Journal of Clinical and Experimental Neuropsychology, 36, 1084-1097. PMID: 25513952; DOI: 10.1080/13803395.2014.983462
Schmitter-Edgecombe, M., *Parsey, C., & Lamb, R. (2014). Development and psychometric properties of the instrumental activities of daily living – compensation scale (IADL-C). Archives of Clinical Neuropsychology, 29, 776-792. DOI: 10.1093/arclin/acu053. PMID 25344901
Schmitter-Edgecombe, M. & Dyck, D. (2014). A cognitive rehabilitation multi-family group intervention for individuals with mild cognitive impairment and their care-partners. Journal of the International Neuropsychological Society, 20, 897-908. PMID 25222630
Schmitter-Edgecombe, M. & *Parsey, C. (2014). Assessment of functional change and cognitive correlates in the progression from normal aging to dementia. Neuropsychology, 28, 881-893. DOI: 10.1037/neu0000109. PMID: 24933485
*Weakley, A., & Schmitter-Edgecombe, M. (2014). Analysis of verbal fluency ability in Alzheimer’s disease: the role of clustering, switching and semantic proximities. Archives of Clinical Neuropsychology, 29, 256-268. DOI: 10.1093/arclin/acu010.
In Press Book Chapters
Schmitter-Edgecombe, M., & Farias, S. T. (forthcoming). Aging and everyday functioning: measurement, correlates and future directions. In G. E. Smith & S. T. Farias (Ed.). APA Handbook of Dementia.
Schmitter-Edgecombe, M., & *Robertson, K. (forthcoming). Naturalistic assessment: everyday environments and emerging technologies. In T. D. Marcotte & I. Grant (Ed.). Neuropsychology of Everyday Functioning (2nd Edition). New York: The Guilford Press.
Schmitter-Edgecombe, M., Cook, D., *Weakley, A. & *Dawadi, P. (forthcoming). Using Smart Environment Technologies to Monitor and Assess Everyday Functioning and Deliver Real-time Intervention. In T. Parsons & R. Kane (Ed.). The Role of Technology in Clinical Neuropsychology. Oxford University Press.
Tam, J., & Schmitter-Edgecombe, M. (forthcoming). A review of factors affecting aging services technology use in the aging population. In T. Parsons & R. Kane (Ed.). The Role of Technology in Clinical Neuropsychology. Oxford University Press.
Current Funded Grants
A clinician-in-the-loop smart technology to support health monitoring and intervention for chronic conditions. NIH: National Institute of Nursing Research. #R01 NINR016732-01A1. 2017-2022. $1,826,091. PI.
Learning-enabled robot support of daily activities for successful activity completion. National Science Foundation: NRI:INT. #NRI-1734558, 2017-2020. $999,998. Co-PI.
Development of an online course suite in tools for analysis of sensor-based behavioral health data (AHA!). NIH: National Institute of Biomedical Imaging and Bioengineering. #R25 EB024327, 2017-2020. $911,650. Co-PI.
Providing support in real-time with smart technologies to improve quality of life. Department of Defense. AZ150096, 2016-2019. $720,663. PI.
GAANN Fellowships for Advancing Interdisciplinary Research, Education and Training in Gerontechnology. US Department of Education: Graduate Assistance in Areas of National Need (GAANN). P200A150115 $590,566. 2015-2018. PI.
The Science of Activity-Predictive Cyber-Physical Systems. National Science Foundation. CPS: TTP Option. #CPS-1543656, 2015-2019, $1,100,000. Co-PI.
Smart Environment Technologies for Health Assessment and Assistance. NIH: National Institute of Biomedical Imaging and Bioengineering. #R01 EB009675, 2014-2018, $1,487,560. PI.
Multidisciplinary Undergraduate Training Program in Health-assistive Smart Environments for Older Adults. NIH: National Institute on Aging. #R25 AG046114, 2014-2019, $1,604,829. PI.
The goal of this research program is to develop cognitive interventions that will help older individuals with progressive neurological disorders (e.g., AD, PD) delay functional disability and increase their quality-of-life. Participants in many of our studies are healthy older adults and early-stage dementia patients who complete standardized neuropsychological tests and cognitive experimental tasks that assess different cognitive skills (e.g., memory, problem-solving). By observing individuals completing complex tasks of daily living in our on-campus smart home environment, we have identified the role that specific memory and executive functioning deficits play in the poorer performances of healthy older adults and individuals with MCI relative to younger adults on complex real-world everyday tasks. We are currently completing a series of studies that involve observing participants completing everyday tasks of daily living as they natural do in their own home and community environments. We are especially interested in learning more about how compensatory strategy use and the role of the environment can support or hinder a person’s ability to remain functionally independent. We expect this work to enhance our intervention work and to assist in creating more ecological valid laboratory-based assessment measures and questionnaires and we are currently evaluating such measures.
Smart Home Assessment and Intervention: We also have several large grants from the National Institute of Health (NIH), the National Science Foundation (NSF) and the Department of Defense (DOD) to support collaborative work with computer scientists and engineers. This work involves developing smart environments and portable technologies for health monitoring and assistance. We are conducting a 5-year longitudinal study of older adults performing daily activities in their own smart homes. By tracking residents’ daily behavior over a long period, we are working to develop intelligent software that can perform automated functional assessment and identify trends that are indicators of acute health changes (e.g., infection, injury) and slower progressive decline (e.g., dementia). We are also working to improve overall health and well-being of residents by delivering prompt-based interventions that support functional independence and promote healthy lifestyle behaviors (e.g., social contact, exercise, regular sleep). In addition, we are working to improve our paper-and pencil notebook by creating a digital memory notebook (DMN) and allowing for real-time intervention by developing a smart home / DMN partnership. Such a partnership would facilitate continued use of a DMN to support functional independence through activity recognition and context-aware prompting, and would offer improved interfaces over the pen-and-paper versions.
Brain Health Intervention: Accumulating evidence suggests that healthy lifestyle factors, as well as cognitive brain training, can help to minimize the effect of cognitive aging. We are piloting holistic brain health intervention being administered in a group format. Older adult participants are being presented with information about healthy lifestyle factors that can influence cognitive aging, including: exercise, nutrition, sleep hygiene, social engagement, stress management, compensatory strategies, assistive technologies, and cognitive engagement. We are also using wearable technologies to track factors such as activity level and sleep. This work builds on a group problem-solving model that we have successfully used in prior work to help teach individuals with mild cognitive impairment and their care-partners to integrate new memory strategies into their everyday lives.
Aging Assistive Technologies: Assistive technologies can increase functional outcome and promote safety as well as reduce caregiver burden and healthcare costs. Despite these positive benefits, there continues to be widespread underutilization of assistive technology in the aging population. One barrier contributing to underutilization is the widespread lack of knowledge about existing supportive technologies, the utility and value of the technologies, as well as how to acquire and use them. With a grant from the Attorney General’s Office of WA, we developed a series of eight videos that cover assistive technologies relevant to the following topics: daily living aids, medication management tools, memory aids, fall prevention devices, hearing devices, vision aids, communication tools and mobility devices. These videos can be found at: tech4aging.wsu.edu. We are working on interventions, including telephone and Web-based interventions, that make use of the video series to increase awareness and use of aging services technologies by older adult users, caregivers and health care professionals
Difficulties with memory, attention and complex problem-solving are common cognitive problems that can occur after someone experiences a traumatic brain injury (TBI). By bridging basic science research with rehabilitation techniques, our work is designed to help persons with TBI overcome cognitive difficulties. A current series of studies focuses on an important goal of rehabilitation, which is to maximize the patient’s ability to function independently and to reintegrate into the home and community. It has been argued that when the rehabilitation environment is more closely connected to the goals and activities that people aspire to complete in their everyday lives, patients will be more motivated to reach their rehabilitation goals and rehabilitation strategies will better generalize to everyday situations. This has led some medical rehabilitation facilitates to invest in simulated community environments, where facsimiles of grocery stores, restaurants, bus stations, cross walks, and recreational venues can help patients make a direct connection to real life challenges. Although theoretical rationale for use of simulated environments is sufficiently strong, there is little empirical support. The purpose of our current work is twofold: First, we are evaluating the efficacy of a newly developed instrument for use in the simulated community, the “Shopping Trip Task,” to predict patient reintegration into the home and community environment. Second, we are evaluating the efficacy of the simulated community environment in the treatment of cognitively impaired patients. We plan to expand this work to include interventions to support awareness of deficits in both patients and family members, and smart technologies for ecological momentary interventions.
Howard Hosick was a professor of Zoology and Genetics at WSU for 34 years. Late in 2004 he began to have memory and administrative function difficulties, and finally in April of 2006 he was diagnosed with early onset Alzheimer’s Disease. He was 62. During that time he found out about a class that was going to be held for people with memory issues and their spouses, given by Dr. Maureen Schmitter-Edgecombe. As a result of this experience, Dr. Hosick was able to use a memory notebook for the next two or three years. Dr. Hosick’s wife, Cynthia, was his primary caregiver. Because of her experience, Dr. Schmitter-Edgecombe invited her to join class panels about memory issues and caregiving challenges, and to participate in some related research to find technology that could be helpful for a memory-impaired person. Dr. Hosick had some research funds remaining after his retirement. The personal help the Hosicks gratefully received from Maureen’s research, and the ensuing friendship between Dr. Schmitter-Edgecombe and Mrs. Hosick, led to the decision to donate the funds to be used for graduate student support in Maureen’s lab.