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Acceptability of collecting speech samples from the elderly via the telephone
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In: Digit Health (2021)
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Applying speech technologies to assess verbal memory in patients with serious mental illness
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24.4 MOVING SPEECH TECHNOLOGY METHODS OUT OF THE LABORATORY: PRACTICAL CHALLENGES AND CLINICAL TRANSLATION OPPORTUNITIES FOR PSYCHIATRY
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An examination of the language construct in NIMH's research domain criteria: Time for reconceptualization!
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What do we really know about blunted vocal affect and alogia? A meta-analysis of objective assessments
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Abstract:
Deficits in nonverbal vocal expression (e.g., blunted vocal affect, alogia) are a hallmark of schizophrenia and are a focus of the Research Domain Criteria initiative from the National Institute of Mental Health. Results from studies using symptom rating scales suggest these deficits are profound; on the order of four to six standard deviations. To complement this endeavor, we conducted a meta-analysis of studies employing objective analysis of natural speech in patients with schizophrenia and nonpsychiatric controls. Thirteen studies, collectively including 480 patients with schizophrenia and 326 nonpsychiatric controls, were identified. There was considerable variability across studies in which aspects of vocal communication were examined and in the magnitudes of deficit. Overall, speech production (reflecting alogia) was impaired at a large effects size level (d = −.80; k = 13), whereas speech variability (reflecting blunted affect) was much more modest (d = −.36; k = 2). Regarding the former, this was largely driven by measures of pause behavior, as opposed to other aspects of speech (e.g., number of words/utterances). On the other hand, ratings of negative symptoms across these studies suggested profound group differences (d = 3.54; k = 4). These data suggest that only certain aspects of vocal expression are affected in schizophrenia, and highlight major discrepancies between symptom rating and objective-based measures. The discussion centers on advancing objective analysis for understanding vocal expression in schizophrenia and for identifying and defining more homogenous patient subsets for study.
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URL: https://doi.org/10.1016/j.schres.2014.09.013 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4254038/ http://www.ncbi.nlm.nih.gov/pubmed/25261880
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Deriving semantic structure from category fluency: clustering techniques and their pitfalls
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The Evolution of the Exponent of Zipf's Law in Language Ontogeny
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An automated method to analyze language use in patients with schizophrenia and their first-degree relatives
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