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Rationale Patient–physician communication plays an essential role in a variety of patient outcomes; however, it is often difficult to operationalize positive patient-physician communication objectively, and the existing evaluation tools are generally time-consuming. Objective This study proposes semantic similarity of the patient's and physician's language in a medical interaction as a measure of patient-physician communication. Latent semantic analysis (LSA), a mathematical method for modeling semantic meaning, was employed to assess similarity in language during clinical interactions between physicians and patients. Methods Participants were 132 Black/African American patients (76% women, Mage = 43.8, range = 18–82) who participated in clinical interactions with 17 physicians (53% women, Mage = 27.1, range = 26–35) in a primary care clinic in a large city in the Midwestern United States. Results LSA captured reliable information about patient-physician communication: The mean correlation indicating similarity between the transcripts of a physician and patient in a clinical interaction was 0.142, significantly greater than zero; the mean correlation between a patient's transcript and transcripts of their physician during interactions with other patients was not different from zero. Physicians differed significantly in the semantic similarity between their language and that of their patients, and these differences were related to physician ethnicity and gender. Female patients exhibited greater communication similarity with their physicians than did male patients. Finally, greater communication similarity was predicted by less patient trust in physicians prior to the interaction and greater patient trust after the interaction. Conclusion LSA is a potentially important tool in patient-physician communication research. Methodological considerations in applying LSA to address research questions in patient-physician communication are discussed.

Psychotic symptoms, defined as the occurrence of delusions or hallucinations, are frequent in Alzheimer disease (AD), affecting ~40 to 60% of individuals with AD (AD with psychosis (AD+P)). In comparison with AD subjects without psychosis, AD+P subjects have more rapid cognitive decline and poor outcomes. Prior studies have estimated the heritability of psychosis in AD at 61%, but the underlying genetic sources of this risk are not known. We evaluated a Discovery Cohort of 2876 AD subjects with (N=1761) or without psychosis (N=1115). All subjects were genotyped using a custom genotyping array designed to evaluate single-nucleotide polymorphisms (SNPs) with evidence of genetic association with AD+P and include SNPs affecting or putatively affecting risk for schizophrenia and AD. Results were replicated in an independent cohort of 2194 AD subjects with (N=734) or without psychosis (N=1460). We found that AD+P is associated with polygenic risk for a set of novel loci and inversely associated with polygenic risk for schizophrenia. Among the biologic pathways identified by the associations of schizophrenia SNPs with AD+P are endosomal trafficking, autophagy and calcium channel signaling. To the best of our knowledge, these findings provide the first clear demonstration that AD+P is associated with common genetic variation. In addition, they provide an unbiased link between polygenic risk for schizophrenia and a lower risk of psychosis in AD. This provides an opportunity to leverage progress made in identifying the biologic effects of schizophrenia alleles to identify novel mechanisms protecting against more rapid cognitive decline and psychosis risk in AD.