Prediction of Relapse in Schizophrenia/Schizoaffective Disorder With Smartphones and On-body Sensors
This trial is active, not recruiting.
|Conditions||schizophrenia, schizoaffective disorder|
|Sponsor||University of Alabama at Birmingham|
|Collaborator||Janssen Research & Development, LLC|
|Start date||August 2014|
|End date||March 2016|
|Trial size||40 participants|
|Trial identifier||NCT02224430, OBSERVESCH4001|
This study is dedicated to achieving a better understanding of how to identify patterns that indicate someone might be at high risk for relapse in schizophrenia or schizoaffective disorder. The investigators are utilizing smartphone technology along with on body sensors to achieve this goal. The study will observe participants behavior in their natural environment for a period of 16 weeks or until a signal of relapse is obtained. Participants will also complete scales in a clinical research environment biweekly.
|Observational model||ecologic or community|
Participants with schizophrenia/schizoaffective disorder will be observed remotely and at weekly/biweekly laboratory visits over a period of 16 weeks or until relapse occurs.
Relapse or exacerbation of symptoms in schizophrenia/schizoaffective disorder
time frame: up to 16 weeks
Male or female participants from 19 years up to 45 years old.
Inclusion Criteria: - DSM - 5 criteria for schizophrenia or schizoaffective disorder based on Diagnostic and Statistical Manual (DSM) criteria - Males and females 19 years or older - Discharged from the University of Alabama at Birmingham (UAB) inpatient psychiatric unit or the emergency department (ER) or currently seen by UAB outpatient physicians - Prescribed and maintained on antipsychotic medication - Psychiatrically stable for a period of at least two weeks - Willingness and capability to comply with the study procedures, including responding to smartphone application prompts, wearing the optional on-body electronic devices - Each participant must activate the Ginger.io User License Agreement (ULA) indicating that he or she understands how data security will be maintained on the smartphones. - Each participant must sign an Informed Consent (ICF) indicating that he or she understands the purpose of the procedures required for the study and are willing to participate in the study Exclusion Criteria: - Physical and or clinical disabilities such as hearing, vision, or motor impairment, which make it impossible to operate a smartphone or respond to prompts (determined using demonstration smartphone for screening) - Inability to understand the consent process as determined by the Evaluation to Give Consent - Substance Use Disorder rating of severe (6 or more symptoms) according to the DSM-5 - Participants with any known skin allergy to the use of adhesives and/or lithium will be excluded from the optional Metria patch segment of the study
|Official title||Remote Physiological, Behavioral and Symptom Assessment Study to Identify Predictors of Symptom Exacerbation and Relapse in Schizophrenia|
|Principal investigator||Adrienne C Lahti, MD|
|Description||This study will follow a group of participants who have recently been discharged from the emergency room or the hospital using several new "high-tech" methods, including the use of a smartphone, health and wellness wristbands/watches and an optional arm patch sensor. These devices (some of which are commercially available to the public for purchase), will capture ongoing physiological information including sweat gland activity, movement, skin temperature, heart rate, breathing rate, and sleep. The smart phone, and an installed application, will administer bidaily and weekly symptom assessment, track the general location of the participant, and collect statistics about text messaging and cell phone use. In addition to the on-body devices participants will come into the clinical research office to complete clinical scales every other week. These scales will be used to determine symptom exacerbation or relapse. This signature will then be utilized as a marker to examine the data collected from the devices. The investigators hope to go beyond clinical evaluation and identify a signature of relapse that is reliably detected from on body devices in a natural setting. This would cut down on the time it takes to successfully treat psychotic illnesses and would reduce the amount of pain and and suffering experienced by patients during relapse.|
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