There are many active research projects accessing and applying shared ADNI data. Use the search above to find specific research focuses on the active ADNI investigations. This information is requested annually as a requirement for data access.
| Principal Investigator | |
| Principal Investigator's Name: | Jeremy Grant |
| Institution: | University of Florida |
| Department: | Clinical & Health Psychology |
| Country: | |
| Proposed Analysis: | The proposed analysis will examine longitudinal cognitive change among older adults (ages 65+) classified as cognitively normal at their initial evaluation and will seek to establish criteria to identify clinically-significant cognitive decline. The analysis will also examine the extent to which demographic characteristics (age, gender, race) and social determinants of health (education, occupational history, social support, geographical markers of socioeconomic status, etc.) predict cognitive change. |
| Additional Investigators | |
| Investigator's Name: | Glenn Smith |
| Proposed Analysis: | The proposed analysis will examine longitudinal cognitive change among older adults (ages 65+) classified as cognitively normal at their initial evaluation and will seek to establish criteria to identify clinically-significant cognitive change in terms of the number of cognitive variables that significantly differ from baseline in an individual. Patterns of cognitive change have been widely studied, but few studies have examined the number of cognitive variables that exceed a change threshold from year-to-year in cognitively-normal individuals or individuals with MCI. The analysis will also examine the extent to which demographic characteristics (age, gender, race) and social determinants of health (education, occupational history, social support, geographical markers of socioeconomic status, etc.) predict cognitive change. |
| Investigator's Name: | Munro Cullum |
| Proposed Analysis: | The proposed analysis will examine longitudinal cognitive change among older adults (ages 65+) classified as cognitively normal at their initial evaluation and will seek to establish criteria to identify clinically-significant cognitive change in terms of the number of cognitive variables that significantly differ from baseline in an individual. Patterns of cognitive change have been widely studied, but few studies have examined the number of cognitive variables that exceed a change threshold from year-to-year in cognitively-normal individuals or individuals with MCI. The analysis will also examine the extent to which demographic characteristics (age, gender, race) and social determinants of health (education, occupational history, social support, geographical markers of socioeconomic status, etc.) predict cognitive change. |
