Digital Migration of the Loewenstein Acevedo Scales for Semantic Interference and Learning (LASSI-L): Development and Validation Study in Older Participants - Philip Harvey; Rosie Curiel-Cid; Peter Kallestrup; Annalee Mueller; Andrea Rivera-Molina; Sara Czaja; Elizabeth Crocco; David Loewenstein (JMIR Mental Health)
Abstract BackgroundThe early detection of mild cognitive impairment is crucial for providing treatment before further decline. Cognitive challenge tests such as the Loewenstein-Acevedo Scales for Semantic Interference and Learning (LASSI-L) can identify individuals at highest risk for cognitive deterioration. Performance on elements of the LASSI-L, particularly proactive interference, correlate with the presence of critical Alzheimer disease biomarkers. However, in-person paper tests require skilled testers and are not practical in many community settings or for large-scale screening in prevention. ObjectiveThis study reports on the development and initial validation of a self-administered computerized version of the Loewenstein-Acevedo Scales for Semantic Interference (LASSI), the digital LASSI (LASSI-D). A self-administered digital version, with an artificial intelligence–generated avatar assistant, was the migrated assessment. MethodsCloud-based software was developed, using voice recognition technology, for English and Spanish versions of the LASSI-D. Participants were assessed with either the LASSI-L or LASSI-D first, in a sequential assessment study. Participants with amnestic mild cognitive impairment (aMCI; n=54) or normal cognition (NC; n=58) were also tested with traditional measures such as the Alzheimer Disease Assessment Scale-Cognition. We examined group differences in performance across the legacy and digital versions of the LASSI, as well as correlations between LASSI performance and other measures across the versions. ResultsDifferences on recall and intrusion variables between aMCI and NC samples on both versions were all statistically significant (all PdPPP ConclusionsThe results for the digital migration of the LASSI-D were highly convergent with the legacy LASSI-L. Across all indices of similarity, including sensitivity, criterion validity, classification accuracy, and performance, the versions converged across languages. Future studies will present additional validation data, including correlations with blood-based Alzheimer disease biomarkers and alternative forms. The current data provide convincing evidence of the use of a fully self-administered digitally migrated cognitive challenge test.