Neurodegenerative disease syndromes often affect personality and interpersonal behavior in addition to cognition, but there are few structured observational measures of altered social demeanor validated for this population. We developed the Social Behavior Observer Checklist (SBOCL), a 3-min checklist tool, to facilitate identification of patterns of interpersonal behavior that are diagnostically relevant to different neurodegenerative syndromes. Research assistants without formal clinical training in dementia used the SBOCL to describe participants' behavior, including 125 healthy older adults and 357 patients diagnosed with one of five neurodegenerative disease syndromes: 135 behavioral variant frontotemporal dementia (bvFTD), 57 semantic variant primary progressive aphasia (svPPA), 51 non-fluent variant PPA (nfvPPA), 65 progressive supranuclear palsy (PSP), and 49 amyloid-positive Alzheimer's disease syndrome (AD), all of whom had concurrent 3D T1 MRI scans available for voxel-based morphometry analysis. SBOCL item interrater reliability ranged from moderate to very high, and score elevations showed syndrome-specific patterns. Subscale scores derived from a degree*frequency product of the items had excellent positive predictive value for identifying patients. Specifically, scores above 2 on the Disorganized subscale, and above 3 on the Reactive and Insensitive subscales, were not seen in any healthy controls but were found in many patients with bvFTD, svPPA, nfvPPA, PSP, and AD syndromes. Both the Disorganized and Reactive subscale scores showed significant linear relationships with frontal and temporal gray matter volume that generalized across syndromes. With these initial psychometric characteristics, the SBOCL may be a useful measure to help non-experts identify patients who are appropriate for additional specialized dementia evaluation, without adding time to patient encounters or requiring the presence of an informant.
Bibliographical noteFunding Information:
Funding for this work was provided by the NIH National Institute on Aging (R01 AG029577, PPG P01 AG1972403, and P50 AG023501), and the Larry L. Hillblom Foundation (2014-A-004-NET).
VBM analyses were performed using the Brainsight system, developed at University of California San Francisco Memory and Aging Center by KR, Cosmo Mielke, and Paul Sukhanov, and powered by the VLSM script written by Stephen M. Wilson, with funding from the Rainwater Charitable Foundation and the UCSF Chancellor’s Fund for Precision Medicine.
© Copyright © 2021 Rankin, Toller, Gavron, La Joie, Wu, Shany-Ur, Callahan, Krassner, Kramer and Miller.
- Alzheimer's disease
- frontotemporal lobar degeneration