Integrating response time and ancillary information into the assessment of anomia - Project Summary/Abstract Anomia is a core feature of aphasia, a disorder affecting 2.5–4 million Americans. Sensitive metrics are needed to support clinical decision making, treatment research, and investigations of the cognitive mechanisms underlying anomia. The first goal of this project is to test a novel psychometric model that will jointly estimate anomia severity and processing speed while taking into account information that is available during the clinical diagnostic process. The second goal is to test a key distributional assumption of response times (RTs) during confrontation naming as a first step towards developing a chronometric model of anomia. Most testing situations possess rich and diverse sources of information, ranging from the psycholinguistic properties of the items to the patient’s accuracy and RTs during various tasks designed to tap a range of cognitive-linguistic processes. Recently, unified analytical frameworks for clinical data have been proposed that integrate multiple sources of information to enhance clinical inference. To this end, in Specific Aim 1, a hierarchical Bayesian item response theory model will be used to simultaneously quantify anomia severity and processing speed based on accuracy and collateral RTs during confrontation naming. To assess the validity of a clinically useful model, proxy RTs automatically captured by readily available software and hand-annotated RTs will be used. In Specific Aim 2, the model will be extended to infuse predictive information about items (i.e., psycholinguistic properties) and persons (i.e., performance on other tasks) into the model to both enhance its precision and understand the relations among its various components. In Specific Aim 3, we will assess the fit of RTs during confrontation naming to an ex-Gaussian distribution with partial pooling using Bayesian hierarchical modeling with random effects. Consistent with Theme 5 in NIDCD’s 2023-2027 Strategic Plan, this proposal will generate the first measurement model of processing speed during word retrieval, a construct crucial for successful communication yet prohibitively costly to assess in fast-paced clinical settings. Further, the joint estimation of speed and severity will lead to more efficient measurement, thereby decreasing barriers to adopting rigorous psychometric practices in aphasiology and creating an IRT framework that could be easily implementable in clinical and research applications. Harnessing the possibilities of this framework will be a critical step towards computer adaptive testing batteries that will reach high levels of precision while minimizing testing burden for both clinicians and patients and will ultimately allow each task to be administered dynamically and tailored uniquely to each person with aphasia. Finally, assessing the distributional properties of RTs will allow researchers to build in silico models of word retrieval that can account for both the underlying cognitive- linguistic processes and the temporal dynamics of word retrieval in post-stroke anomia.
