Abstract
The process of diagnosing dementia conditions, especially Alzheimer's disease, and the cognitive tests that are involved in this process, are important areas of study. Everyday Cognition (ECog) is one test that can be used as part of Alzheimer's disease diagnosis to measure cognitive decline in different areas. In this study, we investigate two versions of the ECog test: the study partner reported version (ECogSP), and the patient reported version (ECogPT). We compare these, using statistical analysis and machine learning techniques, to create classification models to demonstrate the progression in ECog scores over time by using the Alzheimer's Disease Neuroimaging Initiative longitudinal data repository (ADNI); participants are classed with having normal cognition, mild cognitive impairment, or Alzheimer's disease. We found that participants who are diagnosed with Alzheimer's disease at baseline, or during a subsequent visit, tend to self-report consistent ECogPT scores over time indicating no change in cognitive ability. However, study partners tend to report higher and increasing ECogSP scores on behalf of participants in the same diagnosis category; this would indicate a degradation in the participant's cognitive ability over time, consistent with the progress of Alzheimer's disease.