NCT03714893

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.

Trial Health

35
At Risk

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Trial has exceeded expected completion date
Enrollment
30

participants targeted

Target at below P25 for all trials

Timeline
Completed

Started Oct 2018

Shorter than P25 for all trials

Status
unknown

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

Click on a node to explore related trials.

Study Timeline

Key milestones and dates

Study Start

First participant enrolled

October 1, 2018

Completed
7 days until next milestone

First Submitted

Initial submission to the registry

October 8, 2018

Completed
14 days until next milestone

First Posted

Study publicly available on registry

October 22, 2018

Completed
5 months until next milestone

Primary Completion

Last participant's last visit for primary outcome

April 1, 2019

Completed
2 months until next milestone

Study Completion

Last participant's last visit for all outcomes

June 1, 2019

Completed
Last Updated

October 24, 2018

Status Verified

October 1, 2018

Enrollment Period

6 months

First QC Date

October 8, 2018

Last Update Submit

October 22, 2018

Conditions

Outcome Measures

Primary Outcomes (1)

  • Detecting changes in the mental health condition of psychiatric patients

    The wrist watch using sensors will collect physiological data(Heart Rate Variability), physical data (Steps per day) and behavioral data(Quality of sleep).The algorithm that exists in the watch analyzes the amount of steps, the sleep quality- total sleep versus movement and restful sleep, and the distance travelled.The data collected from the wrist watch will then be transferred to an app located on the participant's smartphone which will enable the investigators to collect and analyze the data using big data analysis.After collecting the data above,the investigators will look for a correlation between changes in the personal digital algorithm and changes in the mental health condition of psychiatric patients

    6 months

Secondary Outcomes (1)

  • Detection of illegal drug usage

    6 months

Interventions

Participants will wear a sensor wrist watch which will collect data

Eligibility Criteria

Age18 Years - 75 Years
Sexall
Healthy VolunteersNo
Age GroupsAdult (18-64), Older Adult (65+)
Sampling MethodProbability Sample
Study Population

Adults ,18-75, who are currently hosipatlized in the psychiatric unit at Sheba Medical Center.

You may qualify if:

  • 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

You may not qualify if:

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

Contact the study team to confirm eligibility.

Sponsors & Collaborators

MeSH Terms

Conditions

Mood Disorders

Condition Hierarchy (Ancestors)

Mental Disorders

Study Design

Study Type
observational
Observational Model
COHORT
Time Perspective
RETROSPECTIVE
Sponsor Type
OTHER GOV
Responsible Party
PRINCIPAL INVESTIGATOR
PI Title
Principal investigator

Study Record Dates

First Submitted

October 8, 2018

First Posted

October 22, 2018

Study Start

October 1, 2018

Primary Completion

April 1, 2019

Study Completion

June 1, 2019

Last Updated

October 24, 2018

Record last verified: 2018-10

Data Sharing

IPD Sharing
Will not share