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Congratulations to Professor Robert Gibbons who received funding for two separate projects from the Substance Abuse and Mental Health Services Administration (SAMHSA) and the National Institute on Aging (NIA) .

You can view the specific details of each project below:

Substance Abuse and Mental Health Services Administration (SAMHSA). Mental and Substance Use Disorders Prevalence Study (MDPS), Grant #FG000030-01, $26,375,940 (Co-I).  The primary site is Research Triangle Institute.

Project Summary: The Mental and Substance Use Disorders Prevalence Study is a surveillance effort designed to produce national estimates of mental and substance use disorders among U.S. adults. The survey will include representation of household and non-household (incarcerated, institutionalized, and homeless) populations. Project Name: Mental and Substance Use Disorders Prevalence Study (MDPS). Population(s) to Be Served: The MDPS will conduct clinical assessments with adults across the United States between the ages of 18 and 65 years. The sample will include adults residing both in household (including group quarters) and non-household populations. Non-household populations will include the incarcerated (prisons, jails), institutionalized (state psychiatric hospitals), and homeless. Sampling procedures will oversample individuals at risk for mental and substance use disorders, particularly nonaffective psychosis. Strategies/Interventions: To obtain accurate estimates of mental and substance use disorders, psychiatric epidemiological surveys will be conducted from (1) a national probability household sample; (2) a national probability sample of incarcerated individuals in prisons; and (3) self-representing samples of individuals sentenced in jails and those residing in homeless shelters and state psychiatric hospitals in New York City; Seattle, Washington; and rural North Carolina. Approximately 100,000 households will be rostered to identify eligible adults to participate in the MDPS study. 56,223 individuals within households and homeless shelters will be screened to identify risk of mental or substance abuse disorders. Facility administrative rosters will be used to identify individuals residing in prisons, jails, and state psychiatric hospitals. Using screening data or facility rosters to identify respondents, trained mental health clinicians will administer clinical interviews to 8,000 individuals from the household and non-household populations. Estimates from the household and non-household samples will then be combined using statistical techniques to yield overall national prevalence estimates of seriously impairing mental and substance use disorders. Project Goals and Measurable Objectives: The MDPS will provide unbiased and precise national estimates of schizophrenia, schizoaffective disorder, bipolar disorder, major depression, post-traumatic stress disorder (PTSD), obsessive-compulsive disorder, and alcohol, benzodiazepine, opioid, stimulant, cannabis, and hallucinogen use disorders among U.S. adults ages 18 to 65.

National Institute of Aging (NIA). Adaptive Testing of Cognitive Function based on multi-dimensional Item Response Theory, Grant #R56 AG066127-01, (PI, $600,000). David Gallo, Chair of the Department of Psychology and Diane Lauderdale, Chair of Public Health Sciences (Co-I). Funding for 1 year in anticipation of a 5 year R01. 

With the aging of the American population, the number of older adults at risk for developing cognitive impairment is staggering. Recent research points to age-related change in cognitive performance beginning as early as age 30, highlighting the potential for early interventions. Cognitive function has long been assessed using standardized cognitive tasks administered via neuropsychological evaluation. However, the traditional way to assess cognitive ability is time consuming, requires trained personnel, and requires an office visit. Identifying decline among younger adults is particularly challenging because it can be masked by item redundancy effects. Here we propose developing a new computerized adaptive test (CAT) to assess cognitive function, designed to be administered on computer platforms, that is based on recent advances in multidimensional item response theory (MIRT), with sensitivity to change over relatively short intervals (e.g., two years) among adults over a wide age range. We are calling it CAT-COG. The CAT-COG will assess global cognitive ability as a primary domain as well as 5 cognitive subdomains: episodic memory, semantic memory, working memory, executive function, and processing speed. Our approach will revolutionize computer-based cognitive testing (ultimately in a platform independent way including smartphones), providing precise estimation of an individual’s ability on these domains with minimal respondent burden, using a sufficiently large bank of items so that the same individual’s cognitive ability can be assessed repeatedly without reusing items or stimuli. This project brings together an accomplished interdisciplinary team of researchers and also builds on the unique resources of the Rush Alzheimer’s Disease Center (RADC). These are the key project steps: (1) We will develop a new 1000 item bank of cognitive tasks suited to computational platforms and test them alongside a standard battery of neuropsychological tests through the RADC, including returning cohort participants and newly recruited younger adults. (2) Based on these data, we will develop a computerized adaptive test (CAT-COG) appropriate for measuring global cognitive function and cognitive subdomains across the life course. (3) We will test and validate the CAT-COG among returning RADC participants. (4) We will study short-term variability of the CAT-COG based on daily assessment for a week to determine learning effects and develop a testing protocol that is immune to such effects.

Public Health Relevance
The ability to detect cognitive decline long before the onset of dementia would expand the possibilities for early interventions. Measuring cognitive change, particularly among persons who are not yet experiencing problems, has a number of challenges including the time and expense of gold-standard neuropsychological testing and the problem that test question familiarity may mask underlying decline in ability. Here we propose using recent statistical advances to build a computerized short adaptive test to measure cognitive function, using an approach that does not use the same questions with each testing so that it is better able to identify underlying change.