Ignite Creation Date:
2024-10-26 @ 3:41 PM
Last Modification Date:
2024-10-26 @ 3:41 PM
Study NCT ID:
NCT06613334
Status:
NOT_YET_RECRUITING
Last Update Posted:
None
First Post:
2024-09-10
Brief Title:
Voice-Based Biomarkers a Novel Approach to Monitoring and Predicting Schizophrenia Relapses
Sponsor:
None
Organization:
None
Study Overview
Official Title:
Automatic Measurement of Antipsychotic Medication Adherence in Schizophrenia Through Speech OBSERVSPEECH
Status:
NOT_YET_RECRUITING
Status Verified Date:
2024-09
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
No
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
OBSERVSPEECH
Brief Summary:
Schizophrenia is a serious psychiatric illness affecting approximately 25 million people worldwide Patients with schizophrenia experience hallucinations auditory illusions disordered thinking movement disorders cognitive impairment and social isolation Treatments with antipsychotics have proven effective in improving their living conditions but poor compliance results in relapses and rehospitalizations for the majority of patients which often results in a worsening of residual symptoms The prevention of these relapses is a major issue in the care of these patients and frequent monitoring is necessary The use of a simple rapid and inexpensive tool to monitor symptoms and treatment effect in schizophrenia could improve the effectiveness of the treatment of these patients and prevent relapses Speech is a good candidate as a biomarker in the monitoring of patients with schizophrenia Schizophrenia is accompanied by speech disorders including poor speech variations in tone or intensity or even difficulties in organizing speech
Detailed Description:
Schizophrenia is a highly complex disease of unknown origin It is characterized by a heterogeneous etiology and variable clinical manifestations Numerous studies have investigated genetic biochemical or neurodevelopmental factors of the pathology without providing a definitive answer The environmental factor is also analyzed especially urban density and pollution Finally the immune pathway in particular neuroinflammation has been studied Certain parasites such as Toxoplasma may be involved in the development of schizophrenia in combination with genetic factors All these studies tend to show that the parasitegeneenvironment association would influence the development of schizophrenia but the origins remain unclear and a more complete knowledge of the pathophysiology is needed to improve diagnosis and patient management through new therapeutic targets
More than 80 of patients with schizophrenia have language abnormalities These abnormalities are manifested in syntax semantics and phonology The most common include monotonous intonation poverty of speech increased pauses lack of spontaneity and disruption of speech coherence As speech is an important factor in social interaction patients have great difficulty in maintaining their social relationships
A major problem in schizophrenia is the discontinuation or misuse of antipsychotic treatment which leads to relapse and additional hospital costs According to a 2013 study 50 of patients discontinue treatment after six months often leading to decompensationsTo avoid relapses clinicans can either administer hetero-questionnaire to monitor the patients symptoms or monitor treatment adherence
To monitor symptoms clinicians have at their disposal various standardized questionnaires such as the PAANS However those tests are time-intensive
To monitor treatment adherence clinicians can use blood drug concentrations as an evidence of compliance although this method is invasive and requires costly administration coordination between healthcare profesionnals and patients There are also several standardized tests to monitor adherence such as the clinician-administered BARS questionnaire and the self-administered BEMIB These measures have often been criticized due to factors such as recall bias and poor self-perception which limit the accuracy of patient reports and overestimate adherence
It is therefore essential to develop new tools to objectively measure evolution of symptoms and treatment effects to detect onset of relapses without increasing the burden on patients daily lives
Speech voice markers stand out because they have characteristics that make it easy to use in clinical practice and can be easily integrated into patients daily lives Advances in signal processing and machine learning algorithms now make it possible to measure the different components of speech phonatory skills articulation the different linguistic levels semantics syntax morphology pragmatics as well as the specific disfluencies of spontaneous speech
These different speech markers have been validated in different neurological and psychiatric pathologies in particular Parkinsons disease Huntingtons disease depression suicidal risk and schizophrenia These markers of speech in psychiatry are now generalizing across languages and are also being taken into patients homes to measure changes in patient states
Distinctive voice characteristics have been a feature of schizophrenia since it was first defined They are often associated with negative symptoms such as the inability to show emotion and with observed social impairments It has been quantitatively observed that people with schizophrenia have poorer speech more pauses distinctive tones and differences in voice intensity
Studies have shown antipsychotics also affect language since patients are dopamine-deficient and blockade of these receptors by antipsychotics would exacerbate language impairments In addition blockade of the striatal dopamine receptor leads to extrapyramidal side effects causing tremors muscle rigidity and tics that interfere with the joint movements required for speech
Therefore voice and language are very good candidates as biomarkers in monitoring both symptoms and treatment effects in schizophrenia to detect onsets of relapses
The aim of this study is to determine whether voice biomarkers can be used to objectively monitor symptoms and treatment effects in schizophrenia in order to detect onset of relapses
More than 80 of patients with schizophrenia have language abnormalities These abnormalities are manifested in syntax semantics and phonology The most common include monotonous intonation poverty of speech increased pauses lack of spontaneity and disruption of speech coherence As speech is an important factor in social interaction patients have great difficulty in maintaining their social relationships
A major problem in schizophrenia is the discontinuation or misuse of antipsychotic treatment which leads to relapse and additional hospital costs According to a 2013 study 50 of patients discontinue treatment after six months often leading to decompensationsTo avoid relapses clinicans can either administer hetero-questionnaire to monitor the patients symptoms or monitor treatment adherence
To monitor symptoms clinicians have at their disposal various standardized questionnaires such as the PAANS However those tests are time-intensive
To monitor treatment adherence clinicians can use blood drug concentrations as an evidence of compliance although this method is invasive and requires costly administration coordination between healthcare profesionnals and patients There are also several standardized tests to monitor adherence such as the clinician-administered BARS questionnaire and the self-administered BEMIB These measures have often been criticized due to factors such as recall bias and poor self-perception which limit the accuracy of patient reports and overestimate adherence
It is therefore essential to develop new tools to objectively measure evolution of symptoms and treatment effects to detect onset of relapses without increasing the burden on patients daily lives
Speech voice markers stand out because they have characteristics that make it easy to use in clinical practice and can be easily integrated into patients daily lives Advances in signal processing and machine learning algorithms now make it possible to measure the different components of speech phonatory skills articulation the different linguistic levels semantics syntax morphology pragmatics as well as the specific disfluencies of spontaneous speech
These different speech markers have been validated in different neurological and psychiatric pathologies in particular Parkinsons disease Huntingtons disease depression suicidal risk and schizophrenia These markers of speech in psychiatry are now generalizing across languages and are also being taken into patients homes to measure changes in patient states
Distinctive voice characteristics have been a feature of schizophrenia since it was first defined They are often associated with negative symptoms such as the inability to show emotion and with observed social impairments It has been quantitatively observed that people with schizophrenia have poorer speech more pauses distinctive tones and differences in voice intensity
Studies have shown antipsychotics also affect language since patients are dopamine-deficient and blockade of these receptors by antipsychotics would exacerbate language impairments In addition blockade of the striatal dopamine receptor leads to extrapyramidal side effects causing tremors muscle rigidity and tics that interfere with the joint movements required for speech
Therefore voice and language are very good candidates as biomarkers in monitoring both symptoms and treatment effects in schizophrenia to detect onsets of relapses
The aim of this study is to determine whether voice biomarkers can be used to objectively monitor symptoms and treatment effects in schizophrenia in order to detect onset of relapses
Study Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
None
Is a FDA Regulated Device?:
None
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?:
None