Schizophrenia Clinical Trial
— EIPSPOfficial title:
Pilot Study of a New Insight Assessment Tool
Verified date | April 2019 |
Source | Hôpital le Vinatier |
Contact | n/a |
Is FDA regulated | No |
Health authority | |
Study type | Interventional |
Schizophrenia is a disease of young adults that affects 1% of the general population. According to numerous studies, it has been estimated that between 50% and 80% of patients with schizophrenia do not consider to have a mental disorder and are therefore not aware of their disorders. A poor degree of insight is associated with poor compliance, a higher number of re-hospitalizations, altered social and relational functioning, and a higher number of suicides and violent behaviors. This is why insight, which is an essential dimension of psychopathology, must be evaluated, as it depends to a large extent on the therapeutic alliance, adherence to treatment, likelihood of relapse and prognosis.
Status | Withdrawn |
Enrollment | 0 |
Est. completion date | April 2, 2020 |
Est. primary completion date | January 2, 2020 |
Accepts healthy volunteers | No |
Gender | All |
Age group | 18 Years to 50 Years |
Eligibility |
Inclusion Criteria: - Diagnosis of schizophrenia - Age from 18 to 50 years old - Stabilized clinical condition (without therapeutic modification during the month prior to inclusion) - French language read, spoken and understood (patient and family member) - Having given his consent - Agreement of the guardian for persons under guardianship - Consent of the relative Exclusion Criteria: - Refusal of patient or legal guardian - Refusal of the loved one - Patient and / or neurological disorder of neurological origin of vascular, infectious or neurodegenerative origin |
Country | Name | City | State |
---|---|---|---|
France | Centre Hospitalier Le Vinatier | Bron Cedex |
Lead Sponsor | Collaborator |
---|---|
Hôpital le Vinatier |
France,
Type | Measure | Description | Time frame | Safety issue |
---|---|---|---|---|
Primary | Concurrent validity of the hetero-evaluation scale by studying its correlation with the results obtained, for the same persons, on the SUMD scale (Scale to Assess Unawareness of Mental Disorder) | Correlation higher than 0.40 in the Bravais-Pearson test between the caregiver's hetero-evaluation scale and the Scale to Assess Understanding of Mental Disorder (SUMD) | two years | |
Secondary | Correlation greater than 0.40 to inter-judge fidelity to Cohen's Kappa test | Inter-judicial fidelity will be measured with Cohen's Kappa test, which is a coefficient to measure the agreement between two qualitative variables with the same modalities. Conventionally, it is used to measure the degree of concordance between the stages Awarded by two judges. It can also be applied to measure an intra-observer agreement. The closer the ratio is to 1, the closer the gap between the observed chord proportion and the theoretical proportion of "random" chords approaches the gap between the perfect tuning of the two observers and their random match. The coefficient is always between -1 and 1 (maximum agreement). |
two years | |
Secondary | Cronbach's alpha coefficient with a value of 0.7 measuring internal consistency | Internal consistency will be measured with the Cronbach alpha coefficient, sometimes referred to simply as the coefficient. Which is a statistic used especially in psychometrics to measure the internal consistency (or reliability) of the questions asked during a test (the answers to the questions on the same subject to be correlated). Its value is between 0 and 1, being considered "acceptable" from 0.7. It therefore allows estimation of the fidelity of the score to a test. |
two years | |
Secondary | Correlation greater than 0.40 at the Bravais-Pearson test measuring test fidelity, re-testing | This coefficient makes it possible to detect the presence or absence of a linear relationship between two continuous quantitative characters. To calculate this coefficient, one must first calculate the covariance. Covariance is the mean of the product of deviations from the mean. The linear correlation coefficient of two characters X and Y is equal to the covariance of X and Y divided by the product of the standard deviations of X and Y. It can be shown that this coefficient varies between -1 and +1 | two years |
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