M.S. Computer Science
College of Science & Mathematics
Ganesh Baliga, Ph.D.
Committee Member 1
David J. Libon, Ph.D.
Committee Member 2
Andrea Lobo, Ph.D.
Dementia, Mild Cognitive Impairment, Neurocognitive Assessment
Dementia--diagnosis; Medical technology
Clinical Psychology | Computer Sciences
Background: Neuropsychological assessment is designed to identify neurocognitive impairment and has traditionally relied on pen-and-paper tests. The behavior collected from these tests is usually expressed as a total summary score or a score that reflects a restricted number of features that assess errors. There is now interest in coupling traditional paper and pencil tests with digital assessment technology. In this context traditional metrics such as summary scores are still available. However, using digital technology, a host of time-based parameters can now be obtained. These time-based parameters include the total time to complete the task or total time to completion, as well the time necessary to generate all responses within a task or test trial. In addition to a wealth of highly nuance data, audio and video files of patients' behavior can be created. This permits subsequent, downstream data mining to uncover and discover new features and variables of interest. Digital assessment platforms are reliable and inexpensive and can be deployed in virtually any clinical situation such as a comprehensive, outpatient dementia evaluation where detailed assessment is conducted, as well as in a primary medical care setting to screen for neurocognitive difficulty associated with chronic or acute medical illness. Cardiovascular risks such as hypertension, elevated cholesterol, and diabetes are common if not endemic. In addition to increasing the risk for heart attack and stroke, it is now commonly understood that cardiovascular risks also convey risk for dementia such as Alzheimer's disease. Indeed, most insidious onset dementia illness presents with some degree of vascular alteration in the brain. Moreover, chronic cardiovascular is now well known to associate with a variety of neuropsychological disabilities such as executive control.
Objectives: The current research presents data on the Philadelphia Pointing Span Test (PPST), a digital test designed to measure executive abilities. The current research tested two predictions. The first prediction is that indices from the PPST measuring auditory span and mental manipulation will be related to other indices that assess executive abilities, providing some evidence for criterion validity of the PPST as an executive measure. The second prediction is to assess the degree digitally administered and scored PPST indices are related to cardiovascular risks.
Methods: Fifty-one patients from an outpatient ambulatory medical practice were recruited. All participants were assessed with the PPST and the Montreal Cognitive Assessment (MoCA). Statistical analyses of MoCA test performance resulted in neuropsychological indices measuring executive, language, and memory abilities. The PPST was implemented onto an iPad application capable of tracking accuracy and latency between responses. PPST outcome variables of interest included ANY ORDER and SERIAL Order recall, measures of executive abilities related to auditory span and mental manipulation, respectively; and the latency to generate all responses.
Results: Consistent with our first prediction, PPST SERIAL ORDER recall was correlated to the MoCA executive index where reduced MoCA executive performance was seen along with reduced PPST SERIAL ORDER recall. Consistent with our second prediction slower or longer latencies from selected PPST tests items were associated with greater cardiovascular risk. Conclusions: The PPST, a digitally administered and scored test, appears to provide an efficient assessment of executive abilities. The relationship between PPST performance and cardiovascular risk suggests that the PPST may be means to screen for neuropsychological difficulty as related to medical illness in a primary care setting.
Auriemma, Thomas H., "A DIGITAL APPLICATION FOR ASSESSMENT OF NEUROCOGNITIVE DISABILITIES" (2022). Theses and Dissertations. 3018.