ArticleNPJ digital medicine2020
Applying speech technologies to assess verbal memory in patients with serious mental illness.
Article in NPJ digital medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
27 citing papers in PubMed, 2 syntheses or guidelines pooled it, 49 citations in OpenAlex.
- Functional brain abnormalities of cognitive impairments in schizophrenia indicating higher integration of working memory than other domains.Molecular psychiatry · 2026Pooled it
- Speech-based computational approaches for classification and symptom monitoring in schizophrenia spectrum disorders: a systematic review and meta-analysis.BMC psychiatry · 2026Pooled it
- Assessing the use of automatic speech recognition and large language models for individuals with language impairments.Nature communications · 2026Article
- Article
- Application of artificial intelligence in schizophrenia rehabilitation management: a systematic scoping review.Translational psychiatry · 2026Article
- Speech features as potential objective assessment indicators in schizophrenia patients with violence-related symptoms.Frontiers in psychiatry · 2026Article
- An End-to-End Overview of Clinical Speech AI.IEEE transactions on audio, speech, and language processing (2025) · 2026Article
- Measurement of schizophrenia symptoms through speech analysis from PANSS interview recordings.Frontiers in psychiatry · 2025Article
- Scoring story recall for individual differences research: Central details, peripheral details, and automated scoring.Behavior research methods · 2024Article
- Using HIPAA (Health Insurance Portability and Accountability Act)-Compliant Transcription Services for Virtual Psychiatric Interviews: Pilot Comparison Study.JMIR mental health · 2023Article
- Intensive assessment of executive functions derived from performance in cognitive training games.iScience · 2023Article
- Improving the Applicability of AI for Psychiatric Applications through Human-in-the-loop Methodologies.Schizophrenia bulletin · 2022Article
- Natural Language Processing and Psychosis: On the Need for Comprehensive Psychometric Evaluation.Schizophrenia bulletin · 2022Article
- Using automated syllable counting to detect missing information in speech transcripts from clinical settings.Psychiatry research · 2022Article
- Remote cognitive assessment in severe mental illness: a scoping review.Schizophrenia (Heidelberg, Germany) · 2022Article
- Fully automated detection of formal thought disorder with Time-series Augmented Representations for Detection of Incoherent Speech (TARDIS).Journal of biomedical informatics · 2022Article
- Automatic Schizophrenia Detection Using Multimodality Media via a Text Reading Task.Frontiers in neuroscience · 2022Article
- Smart Homes as Enablers for Depression Pre-Diagnosis Using PHQ-9 on HMI through Fuzzy Logic Decision System.Sensors (Basel, Switzerland) · 2021Article
- Digital phenotyping adherence, feasibility, and tolerability in outpatients with schizophrenia.Journal of psychiatric research · 2021Article
- Natural language processing methods are sensitive to sub-clinical linguistic differences in schizophrenia spectrum disorders.NPJ schizophrenia · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 5 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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 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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.