Understanding others as a mediator between verbal memory and negative symptoms in schizophrenia-spectrum disorder

2021 ◽  
Author(s):  
Delphine Raucher-Chéné ◽  
Elisabeth Thibaudeau ◽  
Geneviève Sauvé ◽  
Katie M. Lavigne ◽  
Martin Lepage
Keyword(s):  
Verbal Memory ◽  
Negative Symptoms ◽  
Spectrum Disorder ◽  
Schizophrenia Spectrum Disorder ◽  
Schizophrenia Spectrum

scholarly journals Acoustic speech markers for schizophrenia-spectrum disorders: a diagnostic and symptom-recognition tool

2021 ◽  
pp. 1-11
Author(s):  
J. N. de Boer ◽  
A. E. Voppel ◽  
S. G. Brederoo ◽  
H. G. Schnack ◽  
K. P. Truong ◽  
...  
Keyword(s):  
Negative Symptoms ◽  
Structured Interview ◽  
Diagnostic Value ◽  
Spectrum Disorder ◽  
Psychotic Symptoms ◽  
Schizophrenia Spectrum Disorders ◽  
Schizophrenia Spectrum Disorder ◽  
Speech Technology ◽  
Schizophrenia Spectrum ◽  
Spectrum Disorders

Abstract Background Clinicians routinely use impressions of speech as an element of mental status examination. In schizophrenia-spectrum disorders, descriptions of speech are used to assess the severity of psychotic symptoms. In the current study, we assessed the diagnostic value of acoustic speech parameters in schizophrenia-spectrum disorders, as well as its value in recognizing positive and negative symptoms. Methods Speech was obtained from 142 patients with a schizophrenia-spectrum disorder and 142 matched controls during a semi-structured interview on neutral topics. Patients were categorized as having predominantly positive or negative symptoms using the Positive and Negative Syndrome Scale (PANSS). Acoustic parameters were extracted with OpenSMILE, employing the extended Geneva Acoustic Minimalistic Parameter Set, which includes standardized analyses of pitch (F0), speech quality and pauses. Speech parameters were fed into a random forest algorithm with leave-ten-out cross-validation to assess their value for a schizophrenia-spectrum diagnosis, and PANSS subtype recognition. Results The machine-learning speech classifier attained an accuracy of 86.2% in classifying patients with a schizophrenia-spectrum disorder and controls on speech parameters alone. Patients with predominantly positive v. negative symptoms could be classified with an accuracy of 74.2%. Conclusions Our results show that automatically extracted speech parameters can be used to accurately classify patients with a schizophrenia-spectrum disorder and healthy controls, as well as differentiate between patients with predominantly positive v. negatives symptoms. Thus, the field of speech technology has provided a standardized, powerful tool that has high potential for clinical applications in diagnosis and differentiation, given its ease of comparison and replication across samples.

scholarly journals Predictors of Remission and Recovery in a First-Episode Schizophrenia Spectrum Disorder Sample: 2-Year Follow-up of the OPUS Trial

2008 ◽  
Vol 53 (10) ◽  
pp. 660-670 ◽  
Author(s):  
Lone Petersen ◽  
Anne Thorup ◽  
Johan Øqhlenschlæger ◽  
Torben Øqstergaard Christensen ◽  
Pia Jeppesen ◽  
...  
Keyword(s):  
Substance Abuse ◽  
Negative Symptoms ◽  
Spectrum Disorder ◽  
First Episode ◽  
Schizophrenia Spectrum Disorder ◽  
Adherence To Medication ◽  
Premorbid Adjustment ◽  
Schizophrenia Spectrum ◽  
First Episode Schizophrenia

Objective: To examine the frequency and predictors of good outcome for patients with first-episode schizophrenia spectrum disorder (SSD). Method: We conducted a 2-year follow-up of a cohort of patients ( n = 547) with first-episode SSD. We evaluated the patients on demographic variables, diagnosis, duration of untreated psychosis (DUP), premorbid functioning, psychotic and negative symptoms, substance abuse, adherence to medication, and service use. ORs were calculated with logistic regression analyses. Results: A total of 369 patients (67%) participated in the follow-up interview. After 2 years, 36% remitted and 17% were considered fully recovered. Full recovery was associated with shorter DUP, better premorbid adjustment, fewer negative symptoms at baseline, no substance abuse at baseline, and adherence to medication and OPUS treatment. Conclusions: Several predictive factors were identified, and focus should be on potentially malleable predictors of outcome, for example, reducing DUP and paying special attention to patients who are unlikely to achieve good outcome, for example, patients with a substance abuse problem and poor premorbid adjustment.

scholarly journals Latent Iron Deficiency as a Marker of Negative Symptoms in Patients with First-Episode Schizophrenia Spectrum Disorder

Nutrients ◽  
2018 ◽  
Vol 10 (11) ◽  
pp. 1707 ◽  
Author(s):  
Sung-Wan Kim ◽  
Robert Stewart ◽  
Woo-Young Park ◽  
Min Jhon ◽  
Ju-Yeon Lee ◽  
...  
Keyword(s):  
Iron Deficiency ◽  
Negative Symptoms ◽  
Early Stage ◽  
Spectrum Disorder ◽  
First Episode ◽  
Duration Of Treatment ◽  
Schizophrenia Spectrum Disorder ◽  
Dsm 5 ◽  
Schizophrenia Spectrum ◽  
First Episode Schizophrenia

Iron deficiency may alter dopaminergic transmission in the brain. This study investigated whether iron metabolism is associated with negative symptoms in patients with first-episode psychosis. The study enrolled 121 patients with first-episode schizophrenia spectrum disorder, whose duration of treatment was 2 months or less. Negative symptoms were measured using the Positive and Negative Syndrome Scale (PANSS) and Clinician-Rated Dimensions of Psychosis Symptom Severity (Dimensional) scale of the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5). Prominent negative symptoms were defined as moderate or severe negative symptoms on the Dimensional scale of the DSM-5. Iron deficiency was defined as a serum ferritin ≤ 20 ng/mL. Patients with iron deficiency were significantly more likely to have prominent negative symptoms (45.2 vs. 22.2%; p = 0.014) and a higher PANSS negative symptoms score (p = 0.046) than those with normal ferritin levels. Patients with prominent negative symptoms had significantly lower ferritin levels (p = 0.025). The significance of these results remained after controlling for the duration of illness and other confounding variables. Our finding of an independent association between iron deficiency and negative symptoms in patients at the very early stage of illness implies that iron dysregulation has an effect on negative symptoms in patients with schizophrenia. The possibility of therapeutic intervention with iron should be further investigated.

scholarly journals Auditory hallucinations, not necessarily a hallmark of psychotic disorder

2017 ◽  
Vol 48 (4) ◽  
pp. 529-536 ◽  
Author(s):  
F. Waters ◽  
J. D. Blom ◽  
R. Jardri ◽  
K. Hugdahl ◽  
I. E. C. Sommer
Keyword(s):  
Psychotic Disorder ◽  
Antipsychotic Medication ◽  
Negative Symptoms ◽  
Spectrum Disorder ◽  
Auditory Hallucinations ◽  
Psychotic Symptoms ◽  
Post Traumatic Stress ◽  
Schizophrenia Spectrum Disorder ◽  
Dsm 5 ◽  
Schizophrenia Spectrum

Auditory hallucinations (AH) are often considered a sign of a psychotic disorder. This is promoted by the DSM-5 category of Other Specified Schizophrenia Spectrum And Other Psychotic Disorder (OSSSOPD), the diagnostic criteria for which are fulfilled with the sole presence of persistent AH, in the absence of any other psychotic symptoms. And yet, persistent AH are not synonymous with having a psychotic disorder, and should therefore not be uncritically treated as such. Many people who seek treatment for persistent AH have no other psychotic symptoms, have preserved reality-testing capacities, and will never develop a schizophrenia spectrum disorder. Instead, hallucinations may be the result of many different causes, including borderline personality disorder, post-traumatic stress disorder (PTSD), hearing loss, sleep disorders or brain lesions, and they may even occur outside the context of any demonstrable pathology. In such cases, the usage of the DSM-5 diagnosis of OSSSOPD would be incorrect, and it may prompt unwarranted treatment with antipsychotic medication. We therefore argue that a DSM-5 diagnosis of Schizophrenia Spectrum Disorder (or any other type of psychotic disorder) characterized by AH should require at least one more symptom listed under the A-criterion (i.e. delusions, disorganized speech, disorganized or catatonic behavior or negative symptoms). Adhering to these more stringent criteria may help to distinguish between individuals with persistent AH which are part of a psychotic disorder, for whom antipsychotic medication may be helpful, and individuals with AH in the absence of such a disorder who may benefit from other approaches (e.g. different pharmacological interventions, improving coping style, trauma-related therapy).

Add-on Antidepressants in the Naturalistic Treatment of Schizophrenia Spectrum Disorder – When, Who, and How?

2017 ◽  
Vol 50 (04) ◽  
pp. 136-144 ◽  
Author(s):  
Rebecca Schennach ◽  
Michael Obermeier ◽  
Florian Seemüller ◽  
Markus Jäger ◽  
Max Schmauss ◽  
...  
Keyword(s):  
Depressive Symptoms ◽  
Side Effects ◽  
Acute Treatment ◽  
Negative Symptoms ◽  
Well Being ◽  
Spectrum Disorder ◽  
Positive Symptoms ◽  
Subjective Well Being ◽  
Schizophrenia Spectrum Disorder ◽  
Schizophrenia Spectrum

Abstract The aim of this study was to evaluate antidepressant add-on treatment within the acute treatment of schizophrenia spectrum disorder patients. Antidepressant add-on was evaluated in 365 patients within a naturalistic multicenter study. Patients with/without antidepressant add-on were compared regarding clinical and treatment-related variables, response and remission, and remission of depressive and negative symptoms. The efficacy of antidepressant add-on treatment was furthermore analyzed applying marginal structure models. Twenty-three percent of the patients received antidepressant add-on for a mean duration of 50.28 (33.42) days. Patients with the diagnosis of a schizoaffective disorder, multiple illness episodes, and a longer duration of their illness as well as those with significantly fewer baseline positive symptoms, more negative and depressive symptoms, more side effects, and less subjective well-being were augmented with antidepressants. At discharge no significant effect of antidepressant add-on treatment was observed in terms of a 25% improvement (p=0.2623), a 50% improvement (p=0.3946), remission (p=0.0552), or remission of depressive (p=0.6336) and negative symptoms (p=0.8756). Also, when analyzing marginal structure models considering the diagnostic subgroups, no significant effect was found. Add-on with antidepressants is common. A final recommendation in terms of this strategy’s efficacy cannot be given.

Sign in / Sign up

Export Citation Format

Share Document