Development and Validation of the Balanced Inventory of Mindfulness-Related Skills (BIMS)

Despite a number of psychometric limitations, the Five Facet Mindfulness Questionnaire (FFMQ) is one of the most widely used measures of mindfulness. Despite its potential to guide improvement of the scale, no multidimensional item response theory (IRT) analysis of the FFMQ has been conducted to date. The present studies fit competing Confirmatory Factor models to different versions of the FFMQ. A 23-item short-form of the FFMQ exhibited the most robust model-to-data fit, however, polytomous bifactor IRT exhibited poor properties, suggesting the need for scale revision. The authors undertook content revision, creating the Balanced-Inventory of Mindfulness-related Skills (BIMS). The BIMS used a structured alternative response format, wherein participants rate which of two response options is more like them, as well as the extent to which it is like them. Confirmatory factor and IRT analyses revealed reasonably good psychometric properties to a 22-item BiFactor scale, consisting of a general and 4 specific (ActAware, Describe, NonJudge, NonReact) factors. The BIMS appears to be a more psychometrically sound revision of the FFMQ, however, it’s representation of the underlying construct of mindfulness continues to be a question for debate

Language as a biomarker for psychosis: A natural language processing approach

Human ratings of conceptual disorganization, poverty of content, referential cohesion and illogical thinking have been shown to predict psychosis onset in prospective clinical high risk (CHR) cohort studies. The potential value of linguistic biomarkers has been significantly magnified, however, by recent advances in natural language processing (NLP) and machine learning (ML). Such methodologies allow for the rapid and objective measurement of language features, many of which are not easily recognized by human raters. Here we review the key findings on language production disturbance in psychosis. We also describe recent advances in the computational methods used to analyze language data, including methods for the automatic measurement of discourse coherence, syntactic complexity, poverty of content, referential coherence, and metaphorical language. Linguistic biomarkers of psychosis risk are now undergoing cross-validation, with attention to harmonization of methods. Future directions in extended CHR networks include studies of sources of variance, and combination with other promising biomarkers of psychosis risk, such as cognitive and sensory processing impairments likely to be related to language. Implications for the broader study of social communication, including reciprocal prosody, face expression and gesture, are discussed

Accelerating Medicines Partnership® Schizophrenia (AMP® SCZ):Rationale and Study Design of the Largest Global Prospective Cohort Study of Clinical High Risk for Psychosis

This article describes the rationale, aims, and methodology of the Accelerating Medicines Partnership® Schizophrenia (AMP® SCZ). This is the largest international collaboration to date that will develop algorithms to predict trajectories and outcomes of individuals at clinical high risk (CHR) for psychosis and to advance the development and use of novel pharmacological interventions for CHR individuals. We present a description of the participating research networks and the data processing analysis and coordination center, their processes for data harmonization across 43 sites from 13 participating countries (recruitment across North America, Australia, Europe, Asia, and South America), data flow and quality assessment processes, data analyses, and the transfer of data to the National Institute of Mental Health (NIMH) Data Archive (NDA) for use by the research community. In an expected sample of approximately 2000 CHR individuals and 640 matched healthy controls, AMP SCZ will collect clinical, environmental, and cognitive data along with multimodal biomarkers, including neuroimaging, electrophysiology, fluid biospecimens, speech and facial expression samples, novel measures derived from digital health technologies including smartphone-based daily surveys, and passive sensing as well as actigraphy. The study will investigate a range of clinical outcomes over a 2-year period, including transition to psychosis, remission or persistence of CHR status, attenuated positive symptoms, persistent negative symptoms, mood and anxiety symptoms, and psychosocial functioning. The global reach of AMP SCZ and its harmonized innovative methods promise to catalyze the development of new treatments to address critical unmet clinical and public health needs in CHR individuals.</p