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: | Taylor Levine |
| Institution: | Washington University |
| Department: | Psychological and Brain Sciences |
| Country: | |
| Proposed Analysis: | Psychometric Properties and Diagnostic Accuracy of ADNI Self- and Informant-Report Spatial Navigation Questions Background. Work from our group has demonstrated that performance on spatial navigation tasks is associated with preclinical AD cross-sectionally and with clinical progression (Allison et al., 2016; Allison et al., 2019; Levine et al., 2020). Using a reliable and valid questionnaire-based measure of spatial navigation developed in the lab, we have found that subjective spatial navigation is associated with CSF measures of amyloid in clinically normal older adults (Allison et al., 2018; Allison et al., 2019). Our work suggests that subjective spatial navigation ability could serve as a potential questionnaire-based screening measure of preclinical AD. Data Requested. We would like to request access to the self- and informant-report items assessing spatial navigation, memory, and divided attention included in the Brain Health Registry. Additionally, we would like to request longitudinal biomarker data (cerebrospinal fluid and PET-PIB) and Clinical Dementia Rating scores. The data would be used to address the following aims: Aim 1. Assess the reliability and validity of self- and informant-reported spatial navigation. Internal consistency will be assessed using Cronbach’s alpha. Test-retest reliability will be assessed using data from multiple time points. Internal consistency will be assessed using Cronbach’s alpha. Convergent validity will be evaluated by conducting a confirmatory factor analysis (CFA). A three-factor structure is hypothesized with spatial navigation, memory, divided attention all loading on to separate factors. Aim 2. Assess diagnostic accuracy of self- and informant-reported spatial navigation in predicting concurrent preclinical AD. Receiver operating characteristics (ROC) analyses, including sensitivity and specificity, will be used to assess the diagnostic accuracy of the spatial navigation items and compare spatial navigation's diagnostic accuracy to that of memory and divided attention. Aim 3. Assess the ability of baseline self- and informant-reported spatial navigation to predict longitudinal clinical decline and AD-biomarker change using hierarchical linear models. |
| Additional Investigators | |
| Investigator's Name: | Denise Head |
| Proposed Analysis: | Psychometric Properties and Diagnostic Accuracy of ADNI Self- and Informant-Report Spatial Navigation Questions Background. Work from our group has demonstrated that performance on spatial navigation tasks is associated with preclinical AD cross-sectionally and with clinical progression (Allison et al., 2016; Allison et al., 2019; Levine et al., 2020). Using a reliable and valid questionnaire-based measure of spatial navigation developed in the lab, we have found that subjective spatial navigation is associated with CSF measures of amyloid in clinically normal older adults (Allison et al., 2018; Allison et al., 2019). Our work suggests that subjective spatial navigation ability could serve as a potential questionnaire-based screening measure of preclinical AD. Data Requested. We would like to request access to the self- and informant-report items assessing spatial navigation, memory, and divided attention included in the Brain Health Registry. Additionally, we would like to request longitudinal biomarker data (cerebrospinal fluid and PET-PIB) and Clinical Dementia Rating scores. The data would be used to address the following aims: Aim 1. Assess the reliability and validity of self- and informant-reported spatial navigation. Internal consistency will be assessed using Cronbach’s alpha. Test-retest reliability will be assessed using data from multiple time points. Internal consistency will be assessed using Cronbach’s alpha. Convergent validity will be evaluated by conducting a confirmatory factor analysis (CFA). A three-factor structure is hypothesized with spatial navigation, memory, divided attention all loading on to separate factors. Aim 2. Assess diagnostic accuracy of self- and informant-reported spatial navigation in predicting concurrent preclinical AD. Receiver operating characteristics (ROC) analyses, including sensitivity and specificity, will be used to assess the diagnostic accuracy of the spatial navigation items and compare spatial navigation's diagnostic accuracy to that of memory and divided attention. Aim 3. Assess the ability of baseline self- and informant-reported spatial navigation to predict longitudinal clinical decline and AD-biomarker change using hierarchical linear models. |
| Investigator's Name: | Samantha Allison |
| Proposed Analysis: | Psychometric Properties and Diagnostic Accuracy of ADNI Self- and Informant-Report Spatial Navigation Questions Background. Work from our group has demonstrated that performance on spatial navigation tasks is associated with preclinical AD cross-sectionally and with clinical progression (Allison et al., 2016; Allison et al., 2019; Levine et al., 2020). Using a reliable and valid questionnaire-based measure of spatial navigation developed in the lab, we have found that subjective spatial navigation is associated with CSF measures of amyloid in clinically normal older adults (Allison et al., 2018; Allison et al., 2019). Our work suggests that subjective spatial navigation ability could serve as a potential questionnaire-based screening measure of preclinical AD. Data Requested. We would like to request access to the self- and informant-report items assessing spatial navigation, memory, and divided attention included in the Brain Health Registry. Additionally, we would like to request longitudinal biomarker data (cerebrospinal fluid and PET-PIB) and Clinical Dementia Rating scores. The data would be used to address the following aims: Aim 1. Assess the reliability and validity of self- and informant-reported spatial navigation. Internal consistency will be assessed using Cronbach’s alpha. Test-retest reliability will be assessed using data from multiple time points. Internal consistency will be assessed using Cronbach’s alpha. Convergent validity will be evaluated by conducting a confirmatory factor analysis (CFA). A three-factor structure is hypothesized with spatial navigation, memory, divided attention all loading on to separate factors. Aim 2. Assess diagnostic accuracy of self- and informant-reported spatial navigation in predicting concurrent preclinical AD. Receiver operating characteristics (ROC) analyses, including sensitivity and specificity, will be used to assess the diagnostic accuracy of the spatial navigation items and compare spatial navigation's diagnostic accuracy to that of memory and divided attention. Aim 3. Assess the ability of baseline self- and informant-reported spatial navigation to predict longitudinal clinical decline and AD-biomarker change using hierarchical linear models. |
