Condition category
Mental and Behavioural Disorders
Date applied
05/02/2016
Date assigned
29/02/2016
Last edited
29/02/2016
Prospective/Retrospective
Retrospectively registered
Overall trial status
Completed
Recruitment status
No longer recruiting

Plain English Summary

Background and study aims
Mental illness is a general term used to describe a range of conditions that affect mood, thoughts and behavior. They are extremely common and it is thought that most people come into contact with mental illness, either directly or indirectly, at some point in their lives. Unlike many physical illnesses, they can be difficult to diagnose as the symptoms can greatly vary from person to person. Data mining is a technique which uses a procedure or formula to solve a problem (algorithm). It is possible that by collecting and analyzing data from people suffering from a mental illness and those who treat them, an algorithm could be used in order make diagnosing patients easier. The aim of this study is to look at a range of different data mining techniques in order to find the best one for helping the diagnosis of mental illness.

Who can participate?
Adults with a mental illness who are being treated at El Mamoura Hospital and the doctors looking after them.

What does the study involve?
Doctors interview a number of in-patients with mental health problems who are being treated at El Mamoura Hospital using a specially designed survey. The data from these surveys is then entered into a computer so that it can be analysed using a number of different data mining techniques. This involves putting the data into different formulas so that any patterns can be identified by the different algorithms. At the end of the study, the accuracy of these techniques are compared by seeing how well the results of the techniques matches with the patients current diagnosis.

What are the possible benefits and risks of participating?
There are no direct benefits or risks to participants taking part in this study.

Where is the study run from?
El Mamoura Hospital for Psychiatric and Addiction Treatment (Egypt)

When is the study starting and how long is it expected to run for?
August 2015 to November 2015

Who is funding the study?
Arab Academy for Science, Technology, and Maritime Transport (Egypt)

Who is the main contact?
Ms Horeya Abou Warda

Trial website

Contact information

Type

Scientific

Primary contact

Ms Horeya Abou Warda

ORCID ID

http://orcid.org/0000-0003-0957-4011

Contact details

Arab Academy for Science
Technology
and Maritime Transport
Abu Quir
Alexandria
21524
Egypt

Additional identifiers

EudraCT number

ClinicalTrials.gov number

Protocol/serial number

N/A

Study information

Scientific title

Diagnosis of psychiatric patients using data mining techniques

Acronym

Study hypothesis

The aim of this study is to identify the best data mining technique to facilitate psychiatric diagnosis.

Ethics approval

General Secretariat of Mental Health and Addiction Treatment (GSMHAT), Ministry of Health and Population (Egypt), 17/08/2015, ref: 1860|8/17

Study design

Single-centre observational cross-sectional study

Primary study design

Interventional

Secondary study design

Randomised controlled trial

Trial setting

Hospitals

Trial type

Diagnostic

Patient information sheet

Not available in web format, please use the contact details below to request a patient information sheet.

Condition

Mental disorders

Intervention

Clinicians interview a number of inpatients at El Mamoura Hospital that are known to have a psychiatric condition, assessing them with the help of a survey that the clinicians complete.
This data is then used to test a number of different data mining techniques (i.e. Random Forest, Decision Tree, Neural Networks, K Nearest Neighbour and Support Vector Machines) to see which was the best one to use to create an automated model for a diagnosing psychiatric conditions.

Intervention type

Behavioural

Phase

Drug names

Primary outcome measures

Identification of the best data mining technique is measured using the accuracy percentage of data mining classification (10-fold cross-validation) after data was collected.

Secondary outcome measures

Classification of psychotic diseases are measured using the accuracy percentage of data mining classification (10-fold cross-validation) after data was collected.

Overall trial start date

17/08/2015

Overall trial end date

30/11/2015

Reason abandoned

Eligibility

Participant inclusion criteria

Patients:
1. Adults
2. Diagnosed with a psychiatric condition (major depression, drug-induced psychosis, schizophrenia, schizoaffective disorder, obsessive – compulsive disorder, bipolar disorder - manic episode and bipolar disorder - mixed episode)
3. Being treated as an inpatient at El Mamoura Hospital
4. Not taking any psychoactive substances

Clinicians:
Clinicians working at the El Mamoura Hospital for psychiatric and addiction treatment.

Participant type

Patient

Age group

Adult

Gender

Both

Target number of participants

1,800 patients.

Participant exclusion criteria

Patients:
1. Not being treated as an inpatient at El Mamoura Hospital
2. Taking psychoactive substances

Clinicians:
Not working at El Mamoura Hospital for psychiatric and addiction treatment

Recruitment start date

15/05/2015

Recruitment end date

17/08/2015

Locations

Countries of recruitment

Egypt

Trial participating centre

El Mamoura Hospital for Psychiatric and Addiction Treatment
Alexandria
21912
Egypt

Sponsor information

Organisation

Arab Academy for Science, Technology, and Maritime Transport

Sponsor details

Abu Quir
Alexandria
21625
Egypt
+20 19838
ccit@aast.edu

Sponsor type

University/education

Website

http://www.aast.edu/en/colleges/ccit/

Funders

Funder type

Government

Funder name

Arab Academy for Science, Technology, and Maritime Transport

Alternative name(s)

Funding Body Type

Funding Body Subtype

Location

Results and Publications

Publication and dissemination plan

Planned publication in an academic journal.

Intention to publish date

Participant level data

Available on request

Results - basic reporting

Publication summary

Publication citations

Additional files

Editorial Notes