Clinical trial NCT03714893: The Analysis of Physical, Physiological and Behavioral Data Collected From Sensors That Track the Mental Condition of Psychiatric Patients
Official title: The Analysis of Physical Physiological and Behavioral Data Collected From Sensors That Track the Mental Condition of Psychiatric Patients Who Are at Risk for Relapse and Who do Not Abide With Their Medication Treatment
Study type: OBSERVATIONAL
Overall status: UNKNOWN
Conditions: Psychiatric Disorders Mood
Lead sponsor: Sheba Medical Center
Sponsor class: OTHER_GOV
First posted: 2018-10-22
Enrollment: 30
Sex: ALL
Minimum age (years): 18
Maximum age (years): 75
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: COHORT
Time perspective: RETROSPECTIVE
Sampling method: PROBABILITY_SAMPLE
Study population: Adults ,18-75, who are currently hosipatlized in the psychiatric unit at Sheba Medical Center.

Brief summary: An observational study that uses a digital system to collect physiological, physical and behavioral data using worn sensors on psychiatric patients suffering from schizophrenia, bipolar and schizoaffective disorders. The system will enable to analyze the data using a personal digital algorithm in order to detect changes in mental condition and or changes in adherence to medication treatment, and assist in identification of illegal drug usage.

Detailed description: An observational study that uses a digital system to collect physiological, physical and behavioral data using worn sensors on psychiatric patients suffering from schizophrenia, bipolar and schizoaffective disorders. It is a known fact that patients suffering from these disorders are more prone to changes in their mental health condition. Sometimes this change is due to change in medical treatment(whether it was the doctor's decision or low adherence to medication treatment).The mental health condition influences physiological, physical and behavioral aspects which could be detected through the personal digital algorithm and could prevent psychiatric deterioration. For example, in a case of a person in a manic episode investigators would expect to find changes in the personal digital algorithm in physiological aspects(increased heart rate, elevated Heart Rate Variability), physical aspects such as increased number of steps per day, and behavioral aspects(increased hours spent outside of home, excessive activity). An early detection can help in the prevention of psychiatric deterioration in this case and help minimize the suffering caused to the patient and caregivers and perhaps assist in minimizing the need for hospitalization.

The data will be collected using wrist watches. The sensors will collect the physiological data(Heart Rate Variability), physical data(number of steps per day) and the behavioral data(quality of sleep). This data will then be collected and analyzed through big data analysis.

Eligibility criteria: Inclusion Criteria:

* Psychiatric patients diagnosed with schizophrenia, bipolar, or schizoaffective disorder according to the DSM 5
* PANSS and CGI scores are 4 and above
* Participants must have the ability to informed consent
* Own a smartphone android 2.3 or IOS 2010 and above

Exclusion Criteria:

* Violent or suicidal participant
* Terminal illness
* Dialysis treatment
* Participants who have a legal guardian
* Participants who do not own a personal smartphone

Primary outcomes:
measure: Detecting changes in the mental health condition of psychiatric patients
timeFrame: 6 months
Secondary outcomes:
measure: Detection of illegal drug usage
timeFrame: 6 months
Other outcomes:
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