Verbal memory deficits are some of the most profound neurocognitive deficits associated with schizophrenia and serious mental illness in general. As yet, their measurement in clinical settings is limited to traditional tests that allow for limited administrations and require substantial resources to deploy and score. Therefore, we developed a digital ambulatory verbal memory test with automated ...

The National Institute of Mental Health’s Research Domain Criteria (RDoC) Initiative “calls for the development of new ways of classifying psychopathology based on dimensions of observable behavior.” As aresult of this ambitious initiative, language has been identifi d as an independent construct in the RDoC matrix. In this article, we frame language within an evolutionary and neuro- ...

Poor social connection or loneliness is a prominent feature of schizotypy and may exacerbate psychosis risk. Previous studies have examined the inter-relationships between loneliness and psychosis risk, but critically, they have largely been conducted in non-clinical samples or exclusively used laboratory questionnaires with limited consideration of the heterogeneity within schizotypy (i.e., positive, ...

<p><i>Background and Hypothesis:</i> Despite decades of “proof of concept” findings supporting the use of Natural Language Processing (NLP) in psychosis research, clinical implementation has been slow. One obstacle reflects the lack of comprehensive psychometric evaluation of these measures. There is overwhelming evidence that criterion and content validity can be achieved for many purposes, ...

Accurate prediction of risk-states in Serious Mental Illnesses (SMIs) is critical for reducing their massive societal burden. Risk-state assessments are notably inaccurate. Recent innovations, including widely available and inexpensive mobile technologies for ambulatory “biobehavioral” data, can reshape risk assessment. To help understand and accelerate clinician involvement, we surveyed 90 ...

Modern advances in computational language processing methods have enabled new approaches to the measurement of mental processes. However, the field has primarily focused on model accuracy in predicting performance on a task or a diagnostic category. Instead the field should be more focused on determining which computational analyses align best with the targeted neurocognitive/psychological functions ...

Natural language processing (NLP) is a multidisciplinary field that involves objectifying aspects of language. Specifically, it understands human language by leveraging statistical and linguistic knowledge. NLP’s potential for enhancing the administration, accuracy, and objectivity of clinical assessments in psychiatry has been touted, as well as its potential for promoting equity in health care. ...

Speech rate and quantity reflect clinical state; thus automated transcription holds potential clinical applications. We describe two datasets where recording quality and speaker characteristics affected transcription accuracy. Transcripts of low-quality recordings omitted significant portions of speech. An automated syllable counter estimated actual speech output and quantified the amount of ...