ArticleDepression and anxiety2019
Research Domain Criteria scores estimated through natural language processing are associated with risk for suicide and accidental death.
Article in Depression and anxiety, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 3 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
22 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Natural language processing with machine learning methods to analyze unstructured patient-reported outcomes derived from electronic health records: A systematic review.Artificial intelligence in medicine · 2023Pooled it
- Diversity in Machine Learning: A Systematic Review of Text-Based Diagnostic Applications.Applied clinical informatics · 2022Pooled it
- Artificial Intelligence and Suicide Prevention: A Systematic Review of Machine Learning Investigations.International journal of environmental research and public health · 2020Pooled it
- Alignment of natural language processing-derived RDoC scores with depression, anhedonia, and anxiety in psychiatric electronic health records.NPP - digital psychiatry and neuroscience · 2026Article
- Reasoning language models for more transparent prediction of suicide risk.BMJ mental health · 2025Article
- Dimensional Measures of Psychopathology in Children and Adolescents Using Large Language Models.Biological psychiatry · 2024Article
- Automatically extracting social determinants of health for suicide: a narrative literature review.Npj mental health research · 2024Review
- Digital phenotyping of depression during pregnancy using self-report data.Journal of affective disorders · 2024Observational
- A 50-state survey study of thoughts of suicide and social isolation among older adults in the United States.Journal of affective disorders · 2023Article
- Insomnia and suicide as reported adverse effects of second-generation antipsychotics and mood stabilizers.Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2022Article
- Characteristics of Dimensional Psychopathology in Suicidal Patients With Major Psychiatric Disorders and Its Association With the Length of Hospital Stay: Algorithm Validation Study.JMIR mental health · 2021Article
- Artificial Intelligence for Mental Health Care: Clinical Applications, Barriers, Facilitators, and Artificial Wisdom.Biological psychiatry. Cognitive neuroscience and neuroimaging · 2021Review
- Mood Disorders and Outcomes of COVID-19 Hospitalizations.The American journal of psychiatry · 2021Article
- Domains of the autism phenotype, cognitive control, and rumination as transdiagnostic predictors of DSM-5 suicide risk.PloS one · 2021Article
- Stratifying risk for dementia onset using large-scale electronic health record data: A retrospective cohort study.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2020Article
- Suicide prediction models: a critical review of recent research with recommendations for the way forward.Molecular psychiatry · 2020Review
- Article
- Machine learning methods for developing precision treatment rules with observational data.Behaviour research and therapy · 2019Article
- Mapping of Transdiagnostic Neuropsychiatric Phenotypes Across Patients in Two General Hospitals.Journal of the Academy of Consultation-Liaison PsychiatryArticle
- Dimensional clinical phenotyping usingAlzheimer's & dementia (Amsterdam, Netherlands)Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
backgroundIdentification of individuals at increased risk for suicide is an important public health priority, but the extent to which considering clinical phenomenology improves prediction of longer term outcomes remains understudied. Hospital discharge provides an opportunity to stratify risk using readily available clinical records and details.
methodsWe applied a validated natural language processing tool to generate estimated Research Domain Criteria (RDoC) scores for a cohort of 444,317 individuals drawn from 815,457 hospital discharges between 2005 and 2013. We used survival analysis to examine the association of this risk with suicide and accidental death, adjusted for sociodemographic features.
resultsIn adjusted models, symptoms in each of the five domains contributed to incremental risk (log rank P < 0.001), with greatest increase observed with positive valence. The contribution of each domain to risk was time dependent.
conclusionsRDoC symptom scores parsed from clinical documentation are associated with suicide and illustrates that multiple domains contribute to risk in a time-varying fashion.
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.