scholarly journals Large-Scale Evaluation of the Positive and Negative Syndrome Scale (PANSS) Symptom Architecture in Schizophrenia

Author(s):  
Keane Lim ◽  
Oon-Him Peh ◽  
Zixu Yang ◽  
Gurpreet Rekhi ◽  
Attilio Rapisarda ◽  
...  

Although the Positive and Negative Syndrome Scale (PANSS) is widely utilized in schizophrenia research, variability in specific item loading exist, hindering reproducibility and generalizability of findings across schizophrenia samples. We aim to establish a common metric PANSS factor structure from a large multi-ethnic sample and validate it against a meta-analysis of existing PANSS models. Schizophrenia participants (N = 3511) included in the current study were part of the Singapore Translational and Clinical Research Program (STCRP) and the Clinical Antipsychotic Trials for Intervention Effectiveness (CATIE). Exploratory Factor Analysis (EFA) was conducted to identify the factor structure of PANSS and validated with a meta-analysis (N = 16,171) of existing PANSS models. Temporal stability of the PANSS model and generalizability to individuals at ultra-high risk (UHR) of psychosis were evaluated. A five-factor solution best fit the PANSS data. These were the i) Positive, ii) Negative, iii) Cognitive/disorganization, iv) Depression/anxiety and v) Hostility factors. Convergence of PANSS symptom architecture between EFA model and meta-analysis was observed. Modest longitudinal reliability was observed. The schizophrenia derived PANSS factor model fit the UHR population, but not vice versa. We found that two other domains, Social Amotivation (SA) and Diminished Expression (DE), were nested within the negative symptoms factor. Here, we report one of the largest transethnic factorial structures of PANSS symptom domains (N = 19,682). Evidence reported here serves as crucial consolidation of a common metric PANSS that could aid in furthering our understanding of schizophrenia.

2018 ◽  
Vol 201 ◽  
pp. 85-90 ◽  
Author(s):  
Zixu Yang ◽  
Keane Lim ◽  
Max Lam ◽  
Richard Keefe ◽  
Jimmy Lee

2016 ◽  
Vol 7 ◽  
Author(s):  
Seon-Kyeong Jang ◽  
Hye-Im Choi ◽  
Soohyun Park ◽  
Eunju Jaekal ◽  
Ga-Young Lee ◽  
...  

2017 ◽  
Vol 46 (1) ◽  
pp. 22-32 ◽  
Author(s):  
Xiao-Jing Gu ◽  
Rui Chen ◽  
Chen-Hui Sun ◽  
Wei Zheng ◽  
Xin-Hu Yang ◽  
...  

This study was a meta-analysis of randomized controlled trials (RCTs) of ranitidine as an adjunct for antipsychotic-induced weight gain in patients with schizophrenia. RCTs reporting weight gain or metabolic side effects in patients with schizophrenia were included. Case reports/series, non-randomized or observational studies, reviews, and meta-analyses were excluded. The primary outcome measures were body mass index (BMI) (kg/m2) and body weight (kg). Four RCTs with five study arms were identified and analyzed. Compared with the control group, adjunctive ranitidine was associated with marginally significant reductions in BMI and body weight. After removing an outlier study for BMI, the effect of ranitidine remained significant. Adjunctive ranitidine outperformed the placebo in the negative symptom score of the Positive and Negative Syndrome Scale. Although ranitidine was associated with less frequent drowsiness, other adverse events were similar between the two groups. Adjunctive ranitidine appears to be an effective and safe option for reducing antipsychotic-induced weight gain and improving negative symptoms in patients with schizophrenia. Larger RCTs are warranted to confirm these findings. Trial registration PROSPERO: CRD42016039735


2020 ◽  
Vol 36 (2) ◽  
pp. 427-431
Author(s):  
Aurelie M. C. Lange ◽  
Marc J. M. H. Delsing ◽  
Ron H. J. Scholte ◽  
Rachel E. A. van der Rijken

Abstract. The Therapist Adherence Measure (TAM-R) is a central assessment within the quality-assurance system of Multisystemic Therapy (MST). Studies into the validity and reliability of the TAM in the US have found varying numbers of latent factors. The current study aimed to reexamine its factor structure using two independent samples of families participating in MST in the Netherlands. The factor structure was explored using an Exploratory Factor Analysis (EFA) in Sample 1 ( N = 580). This resulted in a two-factor solution. The factors were labeled “therapist adherence” and “client–therapist alliance.” Four cross-loading items were dropped. Reliability of the resulting factors was good. This two-factor model showed good model fit in a subsequent Confirmatory Factor Analysis (CFA) in Sample 2 ( N = 723). The current finding of an alliance component corroborates previous studies and fits with the focus of the MST treatment model on creating engagement.


2018 ◽  
Vol 11 (4) ◽  
pp. 207-213 ◽  
Author(s):  
Julie Walsh-Messinger ◽  
Daniel Antonius ◽  
Mark Opler ◽  
Nicole Aujero ◽  
Deborah M. Goetz ◽  
...  

2014 ◽  
Vol 36 (4) ◽  
pp. 336-339 ◽  
Author(s):  
Cinthia H. Higuchi ◽  
Bruno Ortiz ◽  
Arthur A. Berberian ◽  
Cristiano Noto ◽  
Quirino Cordeiro ◽  
...  

2020 ◽  
Vol 46 (Supplement_1) ◽  
pp. S179-S179
Author(s):  
Mei San Ang ◽  
Gurpreet Rekhi ◽  
Jimmy Lee

Abstract Background The conceptualization of negative symptoms has been refined in the past decades. Two-factor model comprising Motivation and Pleasure (MAP) and Emotional Expressivity (EE), five-factor model representing five domains of negative symptoms and second-order five-factor model incorporating the two-factor and five-factor models (Anhedonia, Asociality and Avolition regressed on MAP; Blunted Affect and Alogia regressed on EE) have been suggested as latent structure of negative symptoms. In most studies, the item “Lack of Normal Distress” in the Brief Negative Symptom Scale (BNSS) did not fit well in factor models. Nevertheless, the reported correlation and item-total correlation of Distress with other negative symptom domains and BNSS items were not negligible. Emotion deficit was also discussed as a part of negative symptoms conceptualization. As a single item may not be sufficient to represent an underlying construct that is potentially abstract and complex, the Schedule for the Deficit Syndrome (SDS) which comprises “Diminished Emotional Range” that is conceptually relevant to the BNSS Distress was employed. The study aimed to reexamine the conceptualization of negative symptoms by examining the model fit of several models when BNSS Distress and SDS Emotion (EMO) were included in the models using confirmatory factor analyses (CFA). Methods Two-hundred and seventy-four schizophrenia outpatients aged 21–65 were assessed on the BNSS and SDS. In the two-factor models, Restricted Affect, Diminished Emotional Range and Poverty of Speech in SDS and all items in BNSS Blunted Affect and Alogia subscales were regressed on EE, Curbing of Interests, Diminished Sense of Purpose and Diminished Social Drive in SDS and all items in BNSS Anhedonia, Asociality and Avolition subscales were regressed on MAP, without EMO, or with EMO regressed on either EE or MAP. Five-factor models and second-order five-factor models were examined, with or without EMO. Lastly, a six-factor model with EMO manifested by the sixth factor and second-order six-factor models in which EMO was regressed on either EE or MAP were tested. Root mean square error of approximation (RMSEA) <0.08, comparative fit index (CFI) >0.95, the Tucker-Lewis Index (TLI) >0.95, and weighted root-mean-square residual (WRMR) <1.0 indicate good model fit. CFAs were conducted using Mplus version 7.4. Results The two-factor models did not yield adequate fit indices. Five-factor model and second-order five-factor model without EMO had good model fit; five-factor model: RMSEA=0.056 (0.044–0.068), CFI=0.996, TFI=0.995, WRMR=0.718; second-order five-factor model: RMSEA=0.049 (0.036–0.061), CFI=0.997, TFI=0.996, WRMR=0.758. When EMO was included as indicator in one of the factors in the five-factor models, only the model in which EMO was regressed on Alogia yielded adequate fit. Similarly, in the second-order five-factor models, adequate fit indices were observed only when EMO was regressed on Alogia and Blunted Affect. The six-factor model fitted the data well, RMSEA=0.053 (0.042–0.064), CFI=0.996, TFI=0.995, WRMR=0.711. Second-order six-factor model with EMO regressed on EE yielded better model fit than MAP, RMSEA=0.050 (0.039–0.061), CFI=0.996, TFI=0.995, WRMR=0.849. Discussion In line with previous studies, five-factor and second-order five-factor models without EMO fitted the data well. When EMO was included, a six-factor model and a second-order six-factor model in which the sixth factor was regressed on EE showed good model fit. Emotion, motivation and behavior are intertwined. Our results showed that diminished emotion may also be one of the components of negative symptoms, which had higher association with EE than MAP.


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