scholarly journals M117. ELUCIDATING ARCHITECTURE OF NEGATIVE SYNDROME IN SCHIZOPHRENIA

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.

2020 ◽  
pp. 001316442094289
Author(s):  
Amanda K. Montoya ◽  
Michael C. Edwards

Model fit indices are being increasingly recommended and used to select the number of factors in an exploratory factor analysis. Growing evidence suggests that the recommended cutoff values for common model fit indices are not appropriate for use in an exploratory factor analysis context. A particularly prominent problem in scale evaluation is the ubiquity of correlated residuals and imperfect model specification. Our research focuses on a scale evaluation context and the performance of four standard model fit indices: root mean square error of approximate (RMSEA), standardized root mean square residual (SRMR), comparative fit index (CFI), and Tucker–Lewis index (TLI), and two equivalence test-based model fit indices: RMSEAt and CFIt. We use Monte Carlo simulation to generate and analyze data based on a substantive example using the positive and negative affective schedule ( N = 1,000). We systematically vary the number and magnitude of correlated residuals as well as nonspecific misspecification, to evaluate the impact on model fit indices in fitting a two-factor exploratory factor analysis. Our results show that all fit indices, except SRMR, are overly sensitive to correlated residuals and nonspecific error, resulting in solutions that are overfactored. SRMR performed well, consistently selecting the correct number of factors; however, previous research suggests it does not perform well with categorical data. In general, we do not recommend using model fit indices to select number of factors in a scale evaluation framework.


Healthcare ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 587
Author(s):  
Miguel Mora-Pelegrín ◽  
Beatriz Montes-Berges ◽  
María Aranda ◽  
María Agustina Vázquez ◽  
Elena Armenteros-Martínez

The aim of this study was to develop a measure to evaluate the management of empathic capacity. To this end, two studies were conducted. Study 1 (N = 277, 172 females) describes the scale creation procedure, factorial validity, and internal consistency. The exploratory factor analysis yielded a five-factor model with 18 items (62.4% of the variance explained). The dimensions were as follows: D1: identification, D2: incorporation, D3: reverberation, D4: separation, and D5: projection. The internal consistency was good (alpha values ranging from 0.70 to 0.80). Study 2 (N = 480, 323 females) examined the validity (including convergent validity) of the model and the relationships with sociodemographic variables. The five-factor model showed a robust goodness of fit, χ2 = 240.5, p < 0.001, root mean square residual (RMSR) = 0.05. The fit indices were satisfactory, Non-normed fit index (NNFI) = 0.89, comparative fit index (CFI) = 0.90, mean square error of approximation (RMSEA) = 0.04. The convergent validity analysis showed that, as empathy management increased, so too did the empathy level and emotional intelligence. Some differences by age and sex were found. In conclusion, the Empathy Management Scale is a valid and reliable instrument for analyzing the empathic process that allows vulnerabilities and strengths to be estimated, which could improve professional practice in the healthcare context.


2019 ◽  
Vol 38 (1) ◽  
pp. 97-112
Author(s):  
Elizabeth C. Schenk ◽  
Cara Cook ◽  
Shanda Demorest ◽  
Ekaterina Burduli

Climate change poses significant health risks. Nurses assess, treat, and educate patients about health risks. However, nurses' level of awareness, motivation, and behaviors related to climate change and health is not known. This study developed and tested a novel tool measuring these elements. Three hundred fifty-seven nurses responded to the overall survey. Exploratory factor analysis (EFA) assessed the factor structure of the 22-item CHANT survey and Cronbach's alpha estimated internal consistency. A five-factor model was retained through the EFA, demonstrating good model fit (comparative fit index [CFI] = .95, root mean square error of approximation [RMSEA] = .04, standardized root mean square residual [SRMR] = .09), and items were internally consistent (Cronbach's alpha for each subscale >.70). CHANT has been developed and psychometrically examined and is ready for further use and study.


2021 ◽  
pp. 001316442199240
Author(s):  
Chunhua Cao ◽  
Eun Sook Kim ◽  
Yi-Hsin Chen ◽  
John Ferron

This study examined the impact of omitting covariates interaction effect on parameter estimates in multilevel multiple-indicator multiple-cause models as well as the sensitivity of fit indices to model misspecification when the between-level, within-level, or cross-level interaction effect was left out in the models. The parameter estimates produced in the correct and the misspecified models were compared under varying conditions of cluster number, cluster size, intraclass correlation, and the magnitude of the interaction effect in the population model. Results showed that the two main effects were overestimated by approximately half of the size of the interaction effect, and the between-level factor mean was underestimated. None of comparative fit index, Tucker–Lewis index, root mean square error of approximation, and standardized root mean square residual was sensitive to the omission of the interaction effect. The sensitivity of information criteria varied depending majorly on the magnitude of the omitted interaction, as well as the location of the interaction (i.e., at the between level, within level, or cross level). Implications and recommendations based on the findings were discussed.


2021 ◽  
Vol 14 (3) ◽  
pp. 96
Author(s):  
Nina Ryan ◽  
Xinfeng Ruan ◽  
Jin E. Zhang ◽  
Jing A. Zhang

In this paper, we test the applicability of different Fama–French (FF) factor models in Vietnam, we investigate the value factor redundancy and examine the choice of the profitability factor. Our empirical evidence shows that the FF five-factor model has more explanatory power than the FF three-factor model. The value factor remains important after the inclusion of profitability and investment factors. Operating profitability performs better than cash and return-on-equity (ROE) profitability as a proxy for the profitability factor in FF factor modeling. The value factor and operating profitability have the biggest marginal contribution to a maximum squared Sharpe ratio for the five-factor model factors, highlighting the value factor (HML) non-redundancy in describing stock returns in Vietnam.


SAGE Open ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 215824402110013
Author(s):  
Monique O’Bryant ◽  
Prathiba Natesan Batley ◽  
Anthony J. Onwuegbuzie

The aims of this study were to validate an instrument that measured statistics anxiety and to examine how attitudes toward statistics predict statistics anxiety using the Attitudes Toward Statistics (ATS) Scale for a sample of 323 undergraduate social science majors enrolled in colleges and universities in the United States. A confirmatory factor analysis suggested retaining a revised two-factor model of the Statistical Anxiety Scale (SAS) to measure statistics anxiety, namely, help and interpretation anxiety ([Formula: see text] = 49.37, df = 38.13, p = .105, comparative fit index [CFI] = .959, standardized root mean square residual [SRMR] = .035, root mean square error of approximation [RMSEA] = .076). An examination of discriminant validity of the scores of the SAS with scores of the ATS subscales revealed that statistics anxiety and attitudes toward statistics are distinct constructs. Structural equational modeling was used to determine whether attitude toward course and attitude toward field were predictors of examination anxiety and asking for help anxiety. Of the two factors of the ATS scale, attitudes toward field and attitudes toward course, the latter predicted examination anxiety better than the former did, although both were moderate predictors of examination anxiety. We recommend that statistics educators consider the role of statistics anxiety as well as attitudes toward statistics and the field when designing their pedagogical approach.


2021 ◽  
Vol 12 ◽  
Author(s):  
Fabio Ibrahim ◽  
Johann-Christoph Münscher ◽  
Philipp Yorck Herzberg

The Impostor-Profile (IPP) is a six-dimensional questionnaire measuring the Impostor Phenomenon facets. This study aims to test (a) the appropriateness of a total score, (b) measurement invariance (MI) between gender, (c) the reliability of the IPP, and (d) the convergent validity of the IPP subscales. The sample consisted of N = 482 individuals (64% female). To identify whether the scales of the IPP form a total score, we compared four models: (1) six correlating subscales, (2) a general factor model, (3) a second-order model with one second-order factor and six first-order factors, and (4) a bifactorial model with six group factors. The bifactorial model obtained the best fit. This supports the assumption of a total impostor score. The inspection of structural validity between gender subgroups showed configural, metric, and partial scalar MI. Factor mean comparisons supported the assumption that females and males differ in latent means of the Impostor Phenomenon expressions. The omega coefficients showed sufficient reliability (≥0.71), except for the subscale Need for Sympathy. Overall, the findings of the bifactor model fit and construct validity support the assumption that the measurement through total expression is meaningful in addition to the theoretically formulated multidimensionality of the Impostor Phenomenon.


2019 ◽  
Vol 58 ◽  
pp. 1-9 ◽  
Author(s):  
Wolfgang Fleischhacker ◽  
Silvana Galderisi ◽  
István Laszlovszky ◽  
Balázs Szatmári ◽  
Ágota Barabássy ◽  
...  

AbstractBackground:Negative symptoms in schizophrenia are heterogeneous and multidimensional; effective treatments are lacking. Cariprazine, a dopamine D3-preferring D3/D2 receptor partial agonist and serotonin 5-HT1A receptor partial agonist, was significantly more effective than risperidone in treating negative symptoms in a prospectively designed trial in patients with schizophrenia and persistent, predominant negative symptoms.Methods:Using post hoc analyses, we evaluated change from baseline at week 26 in individual items of the Positive and Negative Syndrome Scale (PANSS) and PANSS-derived factor models using a mixed-effects model for repeated measures (MMRM) in the intent-to-treat (ITT) population (cariprazine = 227; risperidone = 227).Results:Change from baseline was significantly different in favor of cariprazine versus risperidone on PANSS items N1-N5 (blunted affect, emotional withdrawal, poor rapport, passive/apathetic social withdrawal, difficulty in abstract thinking) (P <.05), but not on N6 (lack of spontaneity/flow of conversation) or N7 (stereotyped thinking). On all PANSS-derived negative symptom factor models evaluated (PANSS-Factor Score for Negative Symptoms, Liemburg factors, Khan factors, Pentagonal Structure Model Negative Symptom factor), statistically significant improvement was demonstrated for cariprazine versus risperidone (P <.01). Small and similar changes in positive/depressive/EPS symptoms suggested that negative symptom improvement was not pseudospecific. Change from baseline was significantly different for cariprazine versus risperidone on PANSS-based factors evaluating other relevant symptom domains (disorganized thoughts, prosocial function, cognition; P <.05).Conclusions:Since items representing different negative symptom dimensions may represent different fundamental pathophysiological mechanisms, significant improvement versus risperidone on most PANSS Negative Subscale items and across all PANSS-derived factors suggests broad-spectrum efficacy for cariprazine in treating negative symptoms of schizophrenia.


Symmetry ◽  
2020 ◽  
Vol 12 (2) ◽  
pp. 295 ◽  
Author(s):  
Francisco Jareño ◽  
María de la O González ◽  
Laura Munera

This paper studies in depth the sensitivity of Spanish companies’ returns to changes in several risk factors between January 2000 and December 2018 using the quantile regression approach. Concretely, this research applies extensions of the Fama and French three- and five-factor models (1993 and 2015), according to González and Jareño (2019), adding relevant explanatory factors, such as nominal interest rates, the Carhart (1997) risk factor for momentum and for momentum reversal and the Pastor and Stambaugh (2003) traded liquidity factor. Additionally, for robustness, this paper splits the entire sample period into three sub-sample periods (pre-crisis, crisis and post-crisis) to analyse the results according to the economic cycle. The main conclusions of this paper are fourfold: First, these two models have the greatest explanatory power in the extreme quantiles of the return distribution (0.1 and 0.9) and more specifically in the lowest quantile 0.1. Second, the second model, based on the Fama and French five-factor model, shows the highest explanatory power not only in the full period but also in the three sub-periods. Third, the bank BBVA is the company that shows the highest sensitivity to changes in the explanatory factors in most periods because its adjusted R2 is the highest. Fourth, the stage of the economy with the highest explanatory power is the crisis subperiod. Thus, the final conclusion of this paper is that the second model explains best variations in Spanish companies’ returns in crisis stages and low quantiles.


2020 ◽  
Vol 35 (6) ◽  
pp. 785-785
Author(s):  
J Karr ◽  
G Iverson

Abstract Objective Multiple factor analyses have examined the dimensionality of physical, emotional, and cognitive symptoms both before and after a sport-related concussion. The current study compared model fit and measurement invariance of five candidate factor models, including a one-factor model, original four-factor model (cognitive-sensory, vestibular-somatic, sleep-arousal, and affective), alternative four-factor model (cognitive, physical, sleep-arousal, and affective), five-factor model (cognitive-sensory separated), and bifactor model. Method Student athletes (N = 1,554; 56.7&#37; boys; age: M = 16.1 ± 1.2) completed the Post-Concussion Symptoms Scale (PCSS) at preseason baseline and after a suspected concussion. Confirmatory factor analyses were conducted at both time points, with pre-injury to post-injury measurement invariance models (configural, weak, strong, and strict) also examined. Model results were assessed via fit indices (CFI ≥ .90/RMSEA≤.08) and change-in-fit indices (∆CFI ≤ -.01). Results All models other than the one-factor model showed excellent fit before and after concussion (CFIs&gt;.95/RMSEAs &#60; .06). Based on pre-injury to post-injury invariance analyses, full weak invariance was established for both four-factor and the bifactor models, and partial strict invariance was established for each of these models following modifications. Conclusions Support for partial strict invariance indicates that meaningful comparisons can be made between factor means before and after concussion for the four-factor and bifactor models, evidencing the validity of a total symptom score and specific symptom subscales before and after concussion. The alternative four-factor model may offer an improved conceptual framework compared to the original four-factor model, which included a non-intuitive cognitive-sensory factor. These findings could support the development of normative scores for PCSS subscales for use in research and clinical practice.


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