Clinical utility of the Negative Symptom Assessment-16 in individuals with schizophrenia

Identifying psychiatric manifestations in schizophrenia and depression from audio-visual behavioural indicators through a machine-learning approach

Schizophrenia (SCZ) and depression (MDD) are two chronic mental disorders that seriously affect the quality of life of millions of people worldwide. We aim to develop machine-learning methods with objective linguistic, speech, facial, and motor behavioral cues to reliably predict the severity of psychopathology or cognitive function, and distinguish diagnosis groups. We collected and analyzed the speech, facial expressions, and body movement recordings of 228 participants (103 SCZ, 50 MDD, and 75 healthy controls) from two separate studies. We created an ensemble machine-learning pipeline and achieved a balanced accuracy of 75.3% for classifying the total score of negative symptoms, 75.6% for the composite score of cognitive deficits, and 73.6% for the total score of general psychiatric symptoms in the mixed sample containing all three diagnostic groups. The proposed system is also able to differentiate between MDD and SCZ with a balanced accuracy of 84.7% and differentiate patients with SCZ or MDD from healthy controls with a balanced accuracy of 82.3%. These results suggest that machine-learning models leveraging audio-visual characteristics can help diagnose, assess, and monitor patients with schizophrenia and depression.

Negative symptom dimensions and social functioning in Chinese patients with schizophrenia

OBJECTIVE

Negative symptoms can seriously affect social functioning in patients with schizophrenia. However, the role of various components of negative symptoms in social functioning remains unclear. This study aimed to explore the associations among three different dimensions of negative symptoms (i.e., communication, emotion, and motivation) and social functioning to identify potential therapeutic targets.

METHODS

This cross-sectional study enrolled 202 Chinese participants with schizophrenia. Negative symptoms were evaluated using the Negative Symptom Assessment (NSA). Social functioning was represented by the Personal and Social Performance Scale (PSP) total score and employment status. Correlation analysis was conducted to clarify the relationship between negative symptoms and the PSP total score. Regression analysis was performed to explore the determinants of the PSP total score and employment status, considering negative symptoms and possible confounders, such as demographic features, positive symptoms, cognitive symptoms, depressive symptoms, and extrapyramidal side effects.

RESULTS

The PSP total score was correlated with all three dimensions of negative symptoms (i.e., emotion, motivation, and communication; rs = -0.509, -0.662, and -0.657, respectively). Motivation, instead of emotion or communication, predicted both low PSP total scores and unemployment.

CONCLUSION

Social functioning in patients with schizophrenia was significantly related to motivation. Further studies should focus on motivation and consider it as a therapeutic target to improve patients' social functioning.

Association between negative symptom domains and happiness in schizophrenia

OBJECTIVE

The study aimed to examine the association between levels of self-reported happiness and different domains and subdomains of negative symptoms (NS), as well as symptomatic remission in schizophrenia.

METHODS

274 individuals with schizophrenia were assessed on the Subjective Happiness Scale (SHS), Positive and Negative Syndrome Scale and Clinical Assessment Interview for Negative Symptoms (CAINS). Multiple linear regressions were used to examine the association between levels of happiness and increasingly specific CAINS NS domains and subdomains, as well as symptomatic remission.

RESULTS

177 (64.6%) participants rated themselves as happy. NS, specifically motivation and pleasure related to social activities (MAP Social) (B=-0.402, t=-4.805, p<0.001), and depressive symptoms (B=-0.760, t=-7.102, p<0.001) were significantly associated with levels of happiness. Individuals in symptomatic remission rated themselves happier than those who were not in remission (mean composite SHS: 5.10 [SD=1.18] versus 4.61 [SD=1.16], p=0.002).

CONCLUSIONS

In this largest study on happiness in schizophrenia, we found that the MAP domain of NS, MAP social subdomain and depressive symptoms were significantly associated with levels of happiness. Additionally, individuals in symptomatic remission rated themselves happier than those who were not in remission. Symptom management remains important in the holistic care plan for individuals with schizophrenia.

What is the Best Latent Structure of Negative Symptoms in Schizophrenia? A Systematic Review

Background

Determining the best latent structure of negative symptoms in schizophrenia could benefit assessment tools, neurobiological research, and targeted interventions. However, no review systematically evaluated studies that assessed and validated latent models of negative symptoms.

Objective

To identify and evaluate existing latent structure models in the literature of negative symptoms and to determine the best model.

Method

Systematic search of MEDLINE, EMBASE, and Scopus on July 19, 2020, for confirmatory factor analysis models of negative symptoms in patients with schizophrenia. The available evidence was assessed through 2 sets of criteria: (1) study design quality—based on negative symptoms assessment and modeling strategy and (2) psychometric quality and model fit—based on fit indices and factor definition quality.

Results

In total, 22 studies (n = 17 086) from 9 countries were included. Studies differed greatly regarding symptom scales, setting, and sample size (range = 86–6889). Dimensional models included 2–6 factors (median = 4). Twelve studies evaluated competing models and adopted appropriate instruments to assess the latent structure of negative symptoms. The 5-factor and hierarchical models outperformed unitary, 2-factor, and 3-factor models on all direct comparisons, and most of the analyses derived from the Brief Negative Symptom Scale. Considering the quality criteria proposed, 5-factor and hierarchical models achieved excellent fit in just one study.

Conclusions

Our review points out that the 5-factor and hierarchical models represent the best latent structure of negative symptoms, but the immaturity of the relevant current literature may affect the robustness of this conclusion. Future studies should address current limitations regarding psychometric properties and also address biological and clinical validity to refine available models.

Validation of the Chinese Version of the 16-Item Negative Symptom Assessment

PURPOSE

The Negative Symptom Assessment-16 (NSA-16) is an instrument with significant validity and utility for assessing negative symptoms associated with schizophrenia. This study aimed to validate the Chinese version of the NSA-16.

PATIENTS AND METHODS

A total of 172 participants with schizophrenia were assessed with the NSA-16, Scale for Assessment of Negative Symptoms (SANS), Positive and Negative Syndrome Scale (PANSS), Calgary Depression Scale for Schizophrenia (CDSS) and Rating Scale for Extrapyramidal Side Effects (RSESE). The factor structure of the NSA-16 was evaluated via exploratory and confirmatory factor analysis. Cronbach's α and intraclass correlation coefficients were computed. Correlations were evaluated via Spearman correlation coefficient.

RESULTS

The original five-factor model of the NSA-16 did not fit our sample. Exploratory factor analysis followed by confirmatory factor analysis suggested a three-factor structure, consisting of communication, emotion and motivation, with 15 items. The NSA with 15 items was termed as the NSA-15. The NSA-15 showed excellent convergent validity by high correlations with the SANS and PANSS total and negative factor scores and good divergent validity by independence from the PANSS positive factor, CDSS and RSESE. The NSA-15 showed good internal consistency, interrater reliability and test-retest reliability.

CONCLUSION

The NSA-15 is best characterized by a three-factor structure and is valid for assessing negative symptoms of schizophrenia in Chinese individuals.