Clinical trial NCT05601063: Ascertaining Diagnosis Classification With Elicited Speech
Official title: Ascertaining Diagnosis Classification With Elicited Speech
Study type: OBSERVATIONAL
Overall status: COMPLETED
Conditions: Schizophrenia Spectrum and Other Psychotic Disorders
Bipolar and Related Disorders
Depressive Disorder
Anxiety Disorders
Personality Disorders
Attention Deficit Hyperactivity Disorder
Keywords: Psychiatry
language
natural language processing
digital health
Lead sponsor: Northwell Health
Sponsor class: OTHER
Collaborators: name: Winterlight Labs
First posted: 2022-11-01
Enrollment: 255
Sex: ALL
Minimum age (years): 14
Maximum age (years): 50
Standard ages: CHILD
ADULT
Accepts healthy volunteers: yes
Observational model: CASE_CONTROL
Time perspective: CROSS_SECTIONAL
Sampling method: NON_PROBABILITY_SAMPLE
Study population: Patients whose treatment team believes they would be appropriate for a research study will be approached by research staff and the research project will be explained to them in detail. Inpatients will be approached during their admission and after initial stabilization. Outpatients will be approached before or after their scheduled appointments. Educational seminars regarding this study may be held to inform clinicians and staff of our goals and protocol. Potential participants will be made aware that declining participation will not affect their care. Informed consent will be obtained from all those interested in participating in the study.

Brief summary: Cross-sectional observational study of the relationship between speech patterns and psychiatric symptoms and disorders.

Detailed description: Major psychiatric disorders often occur together in the same patient and it can be difficult to distinguish between disorders with overlapping symptoms. The majority of patients with mental illness receive treatment in settings where it is not feasible to conduct detailed diagnostic interviews or neuropsychiatric testing. A cost-effective and efficient tool is needed for accurate diagnosis. Looking at language is an efficient way of making sense of the brain because it is easily observed and reflects brain circuitry. Automated natural language processing (NLP) can help us do this objectively, efficiently, and with high sensitivity. The investigators aim to use linguistic features extracted using natural language processing to aid in diagnostic classification and in predicting dimensional symptoms. This will be done by obtaining clinical diagnoses, language samples, and self-report scales from 604 participants with a variety of psychiatric symptoms. Adolescents will also be included and the investigators will try to predict diagnosis in adolescents using models that were built on adult data.

Eligibility criteria: Inclusion Criteria:

* Speaks with conversational proficiency with conversational proficiency
* Current diagnosis in the medical chart of any of the following. The patient may be in partial but not full remission. Comorbidity among these disorders and other unlisted disorders is expected and allowable.
* Schizophrenia-spectrum disorder - schizophrenia, schizophreniform, schizoaffective disorder, delusional disorder, brief psychotic disorder, or unspecified psychotic disorder
* Bipolar spectrum disorder - bipolar I or II disorder, cyclothymia, unspecified or other specified bipolar disorder
* (Unipolar) Depressive disorder - major depressive disorder, dysthymia, unspecified and other specified depressive disorder
* Anxiety disorder - obsessive-compulsive disorder, generalized anxiety disorder, panic disorder, post-traumatic stress disorder
* Personality disorder - borderline personality disorder
* Attention-Deficit Hyperactivity Disorder
* Healthy comparison subjects
* Age 14 - 50 years
* Has capacity and willing to sign informed consent; if minor, parent is willing to give consent and child is willing to give assent.
* Screening will not include a pregnancy test. Pregnant women will not be screened out of the study because the study procedures are of very low risk overall, and pregnancy does not place the participant or the fetus at any significant risk.
* Minors will be included in the study because diagnostic ambiguity is prevalent before the age of 18 and this patient group is particularly in need of accurate prognosis and treatment. Therefore, it is of vital importance that the conclusions of the study be applicable to minors and that they be included among the participants.

Exclusion Criteria:

* Participants with substance-induced disorders or disorders secondary to a general medical condition will not be included as underlying brain changes may be different from "primary" psychiatric disorders.
* Disorders affecting speech or language, such as aphasia, intellectual disability (IQ\<70), or language disorder, or movement disorders affecting speech like tardive dyskinesia, or physical impairments causing significant distortions to speech
* Serious neurological or endocrine disorder or any medical condition or treatment known to affect the brain and/or language, including but not limited to: neurodegenerative disorders, traumatic brain injury with active symptoms, autism spectrum disorder, encephalitis, epilepsy
* Cognitive or language limitations, or any other factor that would preclude subjects providing informed consent

Primary outcomes:
measure: Speech features from the Winterlight Speech Assessment
timeFrame: Baseline
Secondary outcomes:
measure: Brief Symptom Inventory
timeFrame: Baseline
measure: Patient Health Questionnaire - 9
timeFrame: Baseline
measure: Generalized Anxiety Disorder - 7
timeFrame: Baseline
measure: Prodromal Questionnaire - Brief
timeFrame: Baseline
measure: Scale for the Assessment of Thought Language and Communication
timeFrame: Baseline
Other outcomes:
Locations:
city: Glen Oaks
country: United States
facility: Zucker Hillside Hospital
state: New York
Study officials:
affiliation: Northwell Health, The Feinstein Institutes of Medical Research
name: Sunny X Tang, MD
role: PRINCIPAL_INVESTIGATOR
References: