ascertaining diagnosis classification with elicited speech

Conditions: Schizophrenia Spectrum and Other Psychotic Disorders; Bipolar and Related Disorders; Depressive Disorder; Anxiety Disorders; Personality Disorders; Attention Deficit Hyperactivity Disorder

Summary: cross-sectional observational study of the relationship between speech patterns and psychiatric symptoms and disorders.

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

Keywords: psychiatry language natural language processing digital health