[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"trial:NCT06705179":3,"trial-entities:NCT06705179":117,"trial-summary:NCT06705179":126},{"id":4,"nct_id":4,"org_study_id":5,"brief_title":6,"official_title":7,"overall_status":8,"completion_date":9,"status_verified_date":10,"last_update_date":11,"start_date":12,"sponsor_name":13,"lead_sponsor_class":14,"has_dmc":15,"brief_summary":16,"detailed_description":17,"conditions":18,"keywords":23,"study_type":26,"primary_purpose":27,"phases":28,"enrollment_info":30,"interventions":33,"primary_outcomes":39,"secondary_outcomes":59,"sex":60,"minimum_age":61,"maximum_age":62,"healthy_volunteers":63,"eligibility_criteria":64,"std_ages":78,"locations":81,"central_contacts":109,"overall_officials":112,"references":115,"see_also_links":116},"NCT06705179","1R01MH138895","Can Computational Measures of Task Performance Predict Psychiatric Symptoms and Changes in Symptom Severity Across Time","Leveraging Computationally Derived Measures of Individual Differences in Learning and Decision-making to Predict Psychiatric Diagnosis, Symptoms and Changes in Symptom Severity Across Time","NOT_YET_RECRUITING","2029-12-31","2024-11","2024-11-26","2025-01-01","California Institute of Technology","OTHER",false,"This study investigates the computational mechanisms associated with psychiatric disease dimensions. The study will characterize the relationship between computational parameter estimates of task performance and psychiatric symptoms and diagnoses with a longitudinal approach over a 12 month interval. Participants will be healthy participants recruited through Prolific an on-line crowdsourcing service, and psychiatric patients and healthy participants recruited via UCLA Psychiatry Clinics and UCLA's STAND Program","The goal of computational psychiatry is to gain knowledge about underlying neurocomputational processes that underpin psychiatric disorders and to leverage this knowledge for improving diagnosis and treatment. A key step toward achieving this goal is to develop measures of individual differences in computations obtained from a single individual that are reliable, robust and meaningfully relevant to psychiatric dysfunction. In order to attain these objectives, it is essential we substantiate relationships between candidate computational mechanisms and diagnostic categories, symptom dimensions and treatment outcomes. In the present study, a computational assessment task battery (CAB) will be utilized that is designed to measure individual differences across a multidimensional array of computational processes. The study aims to separate three different variance components contributing to variability in computational parameter estimation: occasion-related variance due to incidental day to day changes in task performance, state-dependent variance that is related to meaningful variation across time in the underlying computations within an individual, and trait-related differences pertaining to stable individual differences in computations across individuals. To accomplish this, repeated assessments will be implemented using this battery across a 1-year interval within an on-line sample, and use hierarchical Bayesian modeling to separate the effect of occasion, state and trait-related variance on these parameter estimates. These variance components will then be related to diagnostic categories, symptom dimensions and symptom severity measures in a diverse cohort of psychiatric patients (mostly with depression, anxiety and OCD) recruited in Southern California. Finally, the relationship will be tracked between the computational parameter estimates and changes in symptoms across time in a subset of these patients. This study promises to significantly advance understanding of how to reliably extract diagnostically relevant computationally-derived measures of cognitive phenotypes that could eventually be migrated to the clinic.",[19,20,21,22],"Behavior","Depressive Disorder","Anxiety Disorders","Obsessive Compulsive Disorder (OCD)",[24,25],"Computational Psychiatry","Behavioral task battery","INTERVENTIONAL","BASIC_SCIENCE",[29],"NA",{"count":31,"type":32},1100,"ESTIMATED",[34],{"type":35,"name":36,"description":37,"armGroupLabels":38},"BEHAVIORAL","Behavioral task performance","Measures of performance on behavioral tasks",[25],[40,44,47,50,53,56],{"measure":41,"description":42,"timeFrame":43},"Changes in DASS depression scale scores","Changes in computational parameter estimates related to gain\u002Floss learning, reward\u002Feffort tradeoff and reward\u002Fpredation risk tradeoffs will correlate with changes in DASS depression scale scores across time.","12 months",{"measure":45,"description":46,"timeFrame":43},"Changes in DASS anxiety scale scores","Changes in computational parameter estimates related to novelty driven exploration and reward\u002Fpredation risk tradeoffs will be correlated with changes in DASS anxiety scale scores",{"measure":48,"description":49,"timeFrame":43},"Changes in OCI-R scores","Changes in computational parameter estimates related to the balance between model-based vs model-free reinforcement-learning will be correlated with changes in OCI-R symptoms across time.",{"measure":51,"description":52,"timeFrame":43},"OCI-R scores","Computational parameter estimates related to the balance between model-based vs model-free reinforcement-learning will be correlated with OCI-R scores.",{"measure":54,"description":55,"timeFrame":43},"DASS depression scale scores","Computational parameter estimates related to gain\u002Floss learning, reward\u002Feffort tradeoff and reward\u002Fpredation risk tradeoffs will correlate with DASS depression scale scores.",{"measure":57,"description":58,"timeFrame":43},"DASS anxiety scale scores","Computational parameter estimates related to novelty driven exploration and reward\u002Fpredation risk tradeoffs will be correlated with DASS anxiety scale scores",[],"ALL","18 Years","65 Years",true,{"inclusion":65,"exclusion":73,"raw_text":77},[66,67,68,69,66,70,71,72,68,69],"Age range of 18 to 65.","Not currently having a psychiatric diagnosis determined after psychiatric evaluation by Drs. Tadayon-Nejad and Wei (both are board certified psychiatrists).","Ability to understand and perform experimental tasks, i.e. basic ability to communicate and comprehend tasks.","Ability to give informed consent.","Psychiatric diagnosis of any type of depressive disorders, any type of anxiety disorders or obsessive-compulsive disorder.","Primary or comorbid bipolar disorders are allowed but only if not in the acute manic phase.","Comorbidity with autism spectrum disorder (ASD) and attention-deficit\u002Fhyperactivity disorder (ADHD) are allowed.",[74,75,76],"Prior history and or current diagnosis of neurological disease.","History or current diagnosis of psychotic disorders.","Currently active substance use disorder.","Inclusion criteria (healthy control participants):\n\n* Age range of 18 to 65.\n* Not currently having a psychiatric diagnosis determined after psychiatric evaluation by Drs. Tadayon-Nejad and Wei (both are board certified psychiatrists).\n* Ability to understand and perform experimental tasks, i.e. basic ability to communicate and comprehend tasks.\n* Ability to give informed consent.\n\nExclusion criteria (healthy control participants):\n\n• Prior history and or current diagnosis of neurological disease.\n\nInclusion criteria (patients):\n\n* Age range of 18 to 65.\n* Psychiatric diagnosis of any type of depressive disorders, any type of anxiety disorders or obsessive-compulsive disorder.\n* Primary or comorbid bipolar disorders are allowed but only if not in the acute manic phase.\n* Comorbidity with autism spectrum disorder (ASD) and attention-deficit\u002Fhyperactivity disorder (ADHD) are allowed.\n* Ability to understand and perform experimental tasks, i.e. basic ability to communicate and comprehend tasks.\n* Ability to give informed consent.\n\nExclusion criteria (patients):\n\n* Prior history and or current diagnosis of neurological disease.\n* History or current diagnosis of psychotic disorders.\n* Currently active substance use disorder.",[79,80],"ADULT","OLDER_ADULT",[82,97],{"facility":83,"city":84,"state":85,"zip":86,"country":87,"contacts":88,"geoPoint":94},"UCLA Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles","Los Angeles","California","90095","United States",[89],{"name":90,"role":91,"phone":92,"email":93},"Reza Tadayon-nejad, MD PhD","CONTACT","310-206-6389","RTadayonNejad@mednet.ucla.edu",{"lat":95,"lon":96},34.05223,-118.24368,{"facility":98,"city":99,"state":85,"zip":100,"country":87,"contacts":101,"geoPoint":106},"California Insitute of Technology","Pasadena","91125",[102],{"name":103,"role":91,"phone":104,"email":105},"John O'Doherty, D Phil","626-395-5981","jdoherty@hss.caltech.edu",{"lat":107,"lon":108},34.14778,-118.14452,[110],{"name":111,"role":91,"phone":104,"email":105},"John P O'Doherty, D.Phil",[113],{"name":111,"affiliation":13,"role":114},"PRINCIPAL_INVESTIGATOR",[],[],{"nct_id":4,"conditions":118,"biomarkers":125},[119,120,121,122,123,124],"Anxiety Disorder","Attention Deficit Hyperactivity Disorder","Autism Spectrum Disorder","Bipolar Disorder","Depressive disorder","Obsessive Compulsive Disorder",[],{"nct_id":4,"found":63,"summary":127,"prompt_version":137},{"design":128,"status":129,"heading":130,"summary":131,"follow_up":132,"word_count":133,"commitments":134,"compensation":135,"drugs_mentioned":136},"This is an interventional study that plans to enroll 1100 participants. It will look at how behavioral task performance relates to psychiatric symptoms over time.","completed","Understanding Psychiatric Symptoms Through Task Performance","This study is looking at how your performance on certain tasks might help us understand psychiatric symptoms like depression, anxiety, and obsessive-compulsive disorder (OCD). Researchers will use behavioral tasks to measure how you perform. The goal is to see if these measurements can predict changes in your symptoms over 12 months. They will measure changes in your depression (DASS depression scale), anxiety (DASS anxiety scale), and OCD symptoms (OCI-R scores) after one year. You can join if you are between 18 and 65 years old. The study is currently unclear about its status and plans to enroll 1100 people.","Participants will be followed for 12 months to measure changes in their symptoms.",99,"Not specified in the trial record.","Not stated in the trial record.",[],"v2"]