The Latent Structure of Negative Symptoms in Schizophrenia

Strauss, Gregory P.; Núñez, Alicia; Ahmed, Anthony O.; Barchard, Kimberly A.; Granholm, Eric; Kirkpatrick, Brian; Gold, James M.; Allen, Daniel N.

doi:10.1001/jamapsychiatry.2018.2475

Cited by 143 publications

(144 citation statements)

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“…Although the items in Anhedonia, Avolition, and Asociality subscales loaded to the same factor in a previous factor analysis in BNSS 9,18,24,26,27 and CAINS, 13 recent studies revealed that five or more factor models fit better than two-factor models in BNSS and CAINS. 28,[33][34][35] This is in line with the following idea in the original NIMH report: "The five domains may have separate neurobiological substrates and may represent separate therapeutic targets." 5 Some of the neurobiological tasks exploring the biological basis specific to the each of the five domains have been adopted in clinical studies.…”

Section: Discussionsupporting

confidence: 74%

<p>Pilot Validation Study of the Japanese Translation of the Brief Negative Symptoms Scale (BNSS)</p>

Hashimoto

Toyomaki

Oka

et al. 2019

NDT

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The brief negative symptoms scale (BNSS) is a concise instrument used to assess negative symptoms of subjects with schizophrenia covering five domains of negative symptoms and is suitable for use in clinical, experimental, and epidemiological settings. The original and translated version of BNSS has thus far been shown to have adequate psychometric properties. This study aimed to examine internal consistency, inter-rater and test-retest reliability, discriminant and convergent validity, and factor structure of the Japanese version of BNSS. Patients and methods: The assessment was performed by 11 raters using interview videos of nine subjects. Reliability was calculated with Cronbach's alpha for internal consistency and intra class correlation coefficient (ICC) for inter-rater reliability. Pearson's correlation coefficients were calculated to estimate the test-retest reliability. In addition to BNSS, Scale for assessment of negative symptoms (SANS) and scale for assessment of positive symptoms (SAPS) was obtained to assess the convergent and discriminant validity. Factor structure was assessed using principle factor analysis. Results: The Japanese BNSS showed excellent internal consistency (Cronbach's alpha=0.95), inter-rater reliability (intra class correlation coefficient=0.97), and test-retest reliability (r=0.94, p<0.001). The convergent validity shown by correlation with SANS total score (r=0.87, p<0.001) and discriminant validity shown by correlation with SAPS total score (r=0.17, p=−0.68) were also good. Principal factor analysis revealed a two-factor structure of BNSS, although the loading of each item differed from that in the literature. Conclusion: Our pilot study demonstrated that Japanese BNSS had good psychometric properties which were achieved with relatively brief training. Further studies with more subjects and raters with various backgrounds recruited from multiple sites are warranted.

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Section: Discussionsupporting

confidence: 74%

<p>Pilot Validation Study of the Japanese Translation of the Brief Negative Symptoms Scale (BNSS)</p>

Hashimoto

Toyomaki

Oka

et al. 2019

NDT

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“…21 Two recent CFA studies suggest that the failure to support the 2-dimension model may be because this model does not capture the complexity of negative symptoms and there may be additional dimensions of relevance. 22,23 Strauss et al 22 used CFA to evaluate the latent structure of the SANS, 24 BNSS, 25 and CAINS. 12 Four CFA models were examined.…”

Section: Introductionmentioning

confidence: 99%

“…The 5-factor and hierarchical models provided excellent fit, with the 5factor model outperforming the hierarchical model. In a follow-up study, 23 we evaluated the validity and cross-cultural invariance of the 5-factor model reported by Strauss et al 22 The 4 aforementioned models were evaluated across 5 cross-cultural samples, with a total n = 1678 (location/language): Italy/Italian, Spain/Spanish, China/Chinese, Switzerland/German, and United States/English. Results replicated the original study, 22 indicating that 1-and 2-factor models provided poor fit for the data, but 5-factor and hierarchical models provided excellent fit.…”

Section: Introductionmentioning

confidence: 99%

“…Support for the 5-factor model across all 3 of the most current negative symptom scales 22 and across a diverse range of cultures and languages 23 in large representative samples raises the possibility that the recent trend toward conceptualizing negative symptoms in relation to the MAP and EXP dimensions 18 does not capture the complexity of the construct, which is best represented by the 5 NIMH consensus domains. Clarifying the latent structure of negative symptoms is important because EFA studies supporting the 2 factors have been influential, informing how researchers search for pathophysiological mechanisms of negative symptoms [27][28][29] and how pharmaceutical companies have recently been approaching targeted treatment development.…”

Section: Introductionmentioning

confidence: 99%

“…The first study included an American sample of outpatients with SZ (n = 201), and the second included a larger validation sample of SZ outpatients from the Italian national study (n = 912). On the basis of the results of recent CFAs supporting a 5-factor structure of negative symptoms, 22,23 it was hypothesized that the community detection network analysis parameter would indicate that the 13 BNSS items cluster into 5 distinct communities corresponding to the 2005 NIMH consensus domains: anhedonia, avolition, asociality, blunted affect, and alogia. In addition, it was hypothesized that the BNSS lack of normal distress item would produce a sixth community that would be separate from the 5 consensus domains.…”

Section: Introductionmentioning

confidence: 99%

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Network Analysis Reveals the Latent Structure of Negative Symptoms in Schizophrenia

Strauss

Esfahlani

Galderisi

et al. 2018

Schizophrenia Bulletin

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Prior studies using exploratory factor analysis provide evidence that negative symptoms are best conceptualized as 2 dimensions reflecting diminished motivation and expression. However, the 2-dimensional model has yet to be evaluated using more complex mathematical techniques capable of testing structure. In the current study, network analysis was applied to evaluate the latent structure of negative symptoms using a community-detection algorithm. Two studies were conducted that included outpatients with schizophrenia (SZ; Study 1: n = 201; Study 2: n = 912) who were rated on the Brief Negative Symptom Scale (BNSS). In both studies, network analysis indicated that the 13 BNSS items divided into 6 negative symptom domains consisting of anhedonia, avolition, asociality, blunted affect, alogia, and lack of normal distress. Separation of these domains was statistically significant with reference to a null model of randomized networks. There has been a recent trend toward conceptualizing the latent structure of negative symptoms in relation to 2 distinct dimensions reflecting diminished expression and motivation. However, the current results obtained using network analysis suggest that the 2-dimensional conceptualization is not complex enough to capture the nature of the negative symptom construct. Similar to recent confirmatory factor analysis studies, network analysis revealed that the latent structure of negative symptom is best conceptualized in relation to the 5 domains identified in the 2005 National Institute of Mental Health consensus development conference (anhedonia, avolition, asociality, blunted affect, and alogia) and potentially a sixth domain consisting of lack of normal distress. Findings have implications for identifying pathophysiological mechanisms and targeted treatments.

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Associations Between Schizophrenia Polygenic Liability, Symptom Dimensions, and Cognitive Ability in Schizophrenia

et al. 2021

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IMPORTANCE Schizophrenia is a clinically heterogeneous disorder. It is currently unclear how variability in symptom dimensions and cognitive ability is associated with genetic liability for schizophrenia.OBJECTIVE To determine whether phenotypic dimensions within schizophrenia are associated with genetic liability to schizophrenia, other neuropsychiatric disorders, and intelligence. DESIGN, SETTING, AND PARTICIPANTSIn a genetic association study, 3 cross-sectional samples of 1220 individuals with a diagnosis of schizophrenia were recruited from community, inpatient, and voluntary sector mental health services across the UK. Confirmatory factor analysis was used to create phenotypic dimensions from lifetime ratings of the Scale for the Assessment of Positive Symptoms, Scale for the Assessment of Negative Symptoms, and the MATRICS Consensus Cognitive Battery. Analyses of polygenic risk scores (PRSs) were used to assess whether genetic liability to schizophrenia, other neuropsychiatric disorders, and intelligence were associated with these phenotypic dimensions. Data collection for the cross-sectional studies occurred between 1993 and 2016. Data analysis for this study occurred between January 2019 and March 2021. MAIN OUTCOMES AND MEASURESOutcome measures included phenotypic dimensions defined from confirmatory factor analysis relating to positive symptoms, negative symptoms of diminished expressivity, negative symptoms of motivation and pleasure, disorganized symptoms, and current cognitive ability. Exposure measures included PRSs for schizophrenia, bipolar disorder, major depression, attention-deficit/hyperactivity disorder, autism spectrum disorder, and intelligence. RESULTSOf the 1220 study participants, 817 were men (67.0%). Participants' mean (SD) age at interview was 43.10 (12.74) years. Schizophrenia PRS was associated with increased disorganized symptom dimension scores in both a 5-factor model (β = 0.14; 95% CI, 0.07-0.22; P = 2.80 × 10 −4 ) and a 3-factor model across all samples (β = 0.10; 95% CI, 0.05-0.15; P = 2.80 × 10 −4 ). Current cognitive ability was associated with genetic liability to schizophrenia (β = −0.11; 95% CI, −0.19 to −0.04; P = 1.63 × 10 −3 ) and intelligence (β = 0.23; 95% CI, 0.16-0.30; P = 1.52 × 10 −10 ). After controlling for estimated premorbid IQ, current cognitive performance was associated with schizophrenia PRS (β = −0.08; 95% CI, −0.14 to −0.02; P = 8.50 × 10 −3 ) but not intelligence PRS. CONCLUSIONS AND RELEVANCEThe findings of this study suggest that genetic liability for schizophrenia is associated with higher disorganized dimension scores but not other symptom dimensions. Cognitive performance in schizophrenia appears to reflect distinct contributions from genetic liabilities to both intelligence and schizophrenia.

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The Latent Structure of Negative Symptoms in Schizophrenia

Cited by 143 publications

References 50 publications

<p>Pilot Validation Study of the Japanese Translation of the Brief Negative Symptoms Scale (BNSS)</p>

<p>Pilot Validation Study of the Japanese Translation of the Brief Negative Symptoms Scale (BNSS)</p>

Network Analysis Reveals the Latent Structure of Negative Symptoms in Schizophrenia

Associations Between Schizophrenia Polygenic Liability, Symptom Dimensions, and Cognitive Ability in Schizophrenia

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