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dc.contributor.authorHolmlund, Terje Bektesevic
dc.contributor.authorChandler, Chelsea
dc.contributor.authorFoltz, Peter W.
dc.contributor.authorCohen, Alex S.
dc.contributor.authorCheng, Jian
dc.contributor.authorBernstein, Jared C.
dc.contributor.authorRosenfeld, Elizabeth P.
dc.contributor.authorElvevåg, Brita
dc.date.accessioned2020-04-03T07:10:22Z
dc.date.available2020-04-03T07:10:22Z
dc.date.issued2020-03-11
dc.description.abstractVerbal 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 scoring, and repeated self-administration via smart devices. One hundred and four adults participated, comprising 25 patients with serious mental illness and 79 healthy volunteers. The study design was successful with high quality speech recordings produced to 92% of prompts (Patients: 86%, Healthy: 96%). The story recalls were both transcribed and scored by humans, and scores generated using natural language processing on transcriptions were comparable to human ratings (R = 0.83, within the range of human-to-human correlations of R = 0.73–0.89). A fully automated approach that scored transcripts generated by automatic speech recognition produced comparable and accurate scores (R = 0.82), with very high correlation to scores derived from human transcripts (R = 0.99). This study demonstrates the viability of leveraging speech technologies to facilitate the frequent assessment of verbal memory for clinical monitoring purposes in psychiatry.en_US
dc.identifier.citationHolmlund TB, Chandler, Foltz PW, Cohen AS, Cheng J, Bernstein, Rosenfeld, Elvevåg B. Applying speech technologies to assess verbal memory in patients with serious mental illness. npj Digital Medicine. 2020;3en_US
dc.identifier.cristinIDFRIDAID 1802199
dc.identifier.doi10.1038/s41746-020-0241-7
dc.identifier.issn2398-6352
dc.identifier.urihttps://hdl.handle.net/10037/17993
dc.language.isoengen_US
dc.publisherNature Researchen_US
dc.relation.ispartofHolmlund, T.B. (2020). Modeling remotely collected speech data: Applications for psychiatry. (Doctoral thesis). <a href=https://hdl.handle.net/10037/17098>https://hdl.handle.net/10037/17098. </a>
dc.relation.journalnpj Digital Medicine
dc.relation.projectIDinfo:eu-repo/grantAgreement/RCN/FRIMEDBIO/231395/Norway/Diagnostic support system development for the monitoring of psychosis//en_US
dc.rights.accessRightsopenAccessen_US
dc.rights.holderCopyright 2020 The Author(s)en_US
dc.subjectVDP::Medical disciplines: 700::Basic medical, dental and veterinary science disciplines: 710en_US
dc.subjectVDP::Medisinske Fag: 700::Basale medisinske, odontologiske og veterinærmedisinske fag: 710en_US
dc.titleApplying speech technologies to assess verbal memory in patients with serious mental illnessen_US
dc.type.versionpublishedVersionen_US
dc.typeJournal articleen_US
dc.typeTidsskriftartikkelen_US
dc.typePeer revieweden_US


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