scholarly journals A Systematic Review and Meta-Analytic Factor Analysis of the Depression Anxiety Stress Scales

2018 ◽  
Author(s):  
Andrew Yui Yeung ◽  
Livia Yuliawati ◽  
Sing-Hang Cheung
Keyword(s):  
Systematic Review ◽  
Factor Structure ◽  
General Factor ◽  
Depression And Anxiety ◽  
Factor Analyses ◽  
Latent Factor ◽  
Bifactor Models ◽  
Best Fitting ◽  
Unidimensional Construct ◽  
Consistent Performance

Despite the increasingly widespread usage of the Depression Anxiety Stress Scales (DASS), its latent factor structure has yet to be reviewed. We thus carried out a systematic review of studies examining the latent factor structure of the DASS, further synthesizing findings by performing meta-analytic factor analyses on the available data from said studies. The literature search was conducted across three databases, yielding 59 articles encompassing 89 factor analyses. Reviewed results varied across factor analytic approaches (EFA vs. CFA) and DASS versions (DASS42 vs. DASS21), though the original 3-factor structure of the DASS was generally supported. However, bifactor models (consisting of a general factor and group factors) were most consistently best-fitting whenever tested, supporting an underlying unidimensional construct in DASS. This notion was corroborated by our meta-analytic factor analyses, wherein DASS21 bifactor models demonstrated the same consistent performance, though DASS42 analyses were inconclusive between a 3-factor and 1-factor solution. Our findings fit in with broader historical and contemporary developments in the field, and reinforce the potential utility of bifactor models in illustrating the overlap between depression and anxiety. Some recommendations moving forward are discussed.

Exploratory Factor Analyses of the Intelligence and Development Scales–2: Implications for Theory and Practice

Assessment ◽  
2019 ◽  
Vol 27 (8) ◽  
pp. 1853-1869 ◽  
Author(s):  
Silvia Grieder ◽  
Alexander Grob
Keyword(s):  
Factor Structure ◽  
Visual Processing ◽  
Mathematical Reasoning ◽  
Factor Loading ◽  
Theory And Practice ◽  
Long Term Memory ◽  
General Factor ◽  
Factor Analyses ◽  
Reliability Estimates ◽  
Exploratory Factor Analyses

The factor structure of the intelligence and scholastic skills domains of the Intelligence and Development Scales–2 was examined using exploratory factor analyses with the standardization and validation sample ( N = 2,030, aged 5 to 20 years). Results partly supported the seven proposed intelligence group factors. However, the theoretical factors Visual Processing and Abstract Reasoning as well as Verbal Reasoning and Long-Term Memory collapsed, resulting in a five-factor structure for intelligence. Adding the three scholastic skills subtests resulted in an additional factor Reading/Writing and in Logical–Mathematical Reasoning showing a loading on abstract Visual Reasoning and the highest general factor loading. A data-driven separation of intelligence and scholastic skills is not evident. Omega reliability estimates based on Schmid–Leiman transformations revealed a strong general factor that accounted for most of the true score variance both overall and at the group factor level. The possible usefulness of factor scores is discussed.

scholarly journals Electronic Health Literacy in Swiss-German Parents: Cross-Sectional Study of eHealth Literacy Scale Unidimensionality (Preprint)

2019 ◽  
Author(s):  
Sibylle Juvalta ◽  
Matthew J Kerry ◽  
Rebecca Jaks ◽  
Isabel Baumann ◽  
Julia Dratva
Keyword(s):  
Health Literacy ◽  
Digital Media ◽  
Factor Structure ◽  
Digital Health ◽  
Cross Sectional Study ◽  
General Factor ◽  
Factor Analyses ◽  
Cross Sectional ◽  
Ehealth Literacy ◽  
Swiss German

BACKGROUND Parents often use digital media to search for information related to their children’s health. As the quantity and quality of digital sources meant specifically for parents expand, parents’ digital health literacy is increasingly important to process the information they retrieve. One of the earliest developed and widely used instruments to assess digital health literacy is the self-reported eHealth Literacy Scale (eHEALS). However, the eHEALS has not been psychometrically validated in a sample of parents. Given the inconsistency of the eHEALS underlying factor structure across previous reports, it is particularly important for validation to occur. OBJECTIVE This study aimed to determine the factor structure of the German eHEALS measure in a sample of parents by adopting classic and modern psychometric approaches. In particular, this study sought to identify the eHEALS validity as a unidimensional index as well as the viability for potential subscales. METHODS A cross-sectional design was used across two purposive sampling frames: online and paper administrations. Responses were collected between January 2018 and May 2018 from 703 Swiss-German parents. In addition to determining the sampling characteristics, we conducted exploratory factor analysis of the eHEALS by considering its ordinal structure using polychoric correlations. This analysis was performed separately for online–based and paper–based responses to examine the general factor strength of the eHEALS as a unidimensional index. Furthermore, item response theory (IRT) analyses were conducted by fitting eHEALS to a bifactor model to further inspect its unidimensionality and subscale viability. RESULTS Parents in both samples were predominantly mothers (622/703, 88.5%), highly educated (538/703, 76.9%), of Swiss nationality (489/703, 71.8%), and living with a partner (692/703, 98.4%). Factor analyses of the eHEALS indicated the presence of a strong general factor across both paper and online samples, and the Wilcoxon rank-sum test indicated that the eHEALS total sum score was not significantly different between the paper and online samples (<i>P</i>=.12). Finally, the IRT analyses indicated negligible multidimensionality, insufficient subscale reliability after accounting for the eHEALS general factor, and a reduced subset of items that could serve as a unidimensional index of the eHEALS across the paper and online samples. CONCLUSIONS The German eHEALS evidenced good psychometric properties in a parent-specific study sample. Factor analyses indicated a strong general factor across purposively distinct sample frames (online and paper). IRT analyses validated the eHEALS as a unidimensional index while failing to find support for subscale usage.

scholarly journals Factorial Invariance in Hierarchical Factor Models of Mental Disorders in African American and European American Youths

2019 ◽  
Author(s):  
Quanfa He ◽  
James Janford Li
Keyword(s):  
Mental Disorders ◽  
Factor Model ◽  
Factorial Invariance ◽  
European American ◽  
General Factor ◽  
Prevalence Rates ◽  
Bifactor Models ◽  
Best Fitting ◽  
Racial Ethnic ◽  
Three Factor

Background: There is converging and compelling evidence that mental disorders are more optimally conceptualized in a hierarchical framework that transcends traditional categorical boundaries. However, the majority of this evidence comes from studies that draw upon predominantly Caucasian populations. Whether the hierarchical conceptualization of mental disorders generalizes across racial-ethnic groups, including for African American (AA) youths, is unclear. This research is especially crucial in light of the observed racial-ethnic differences in the prevalence rates of several mental disorders. Methods: We tested multidimensional and bifactor models of 15 DSM-5 diagnoses and psychiatric traits in two groups, including AA (n=3,088) and European American (EA) (n=5,147) youths aged 8-21 from the Philadelphia Neurodevelopmental Cohort (PNC). We also conducted multigroup confirmatory factor analyses to test for factorial invariance between the best fitting AA and EA multidimensional and bifactor models. Results: In the multidimensional model tests, a three-factor model, specifying internalizing, externalizing, and thought dimensions, emerged as the best fitting model for AAs and EAs. In the bifactor model tests, a three-factor model (i.e., internalizing, externalizing, and thought dimensions) that also specified a general factor emerged as the optimal for both AAs and EAs. The general factor accounted for a significant proportion of the covariation between the secondary factors and the individual disorders and traits. Furthermore, both models were factorially invariant, indicating that there was no significant difference in the factor structure of mental disorders between AAs and EAs in PNC. Conclusions: This study provides evidence that the hierarchical factor structure of mental disorders may be racial-ethnically robust. This finding has implications for etiological and epidemiological studies focused on racial-ethnic subgroup comparisons, particularly with respect to identifying similarities and differences in prevalence rates or sociodemographic risk factors for mental disorders.

scholarly journals Factor Structure and Measurement Invariance Across Gender of the Beck Depression Inventory-II in Adolescent Psychiatric Patients

2020 ◽  
Vol 11 ◽  
Author(s):  
Ferdinand Keller ◽  
Inken Kirschbaum-Lesch ◽  
Joana Straub
Keyword(s):  
Measurement Invariance ◽  
Beck Depression Inventory ◽  
Factor Structure ◽  
Goodness Of Fit ◽  
Clinical Sample ◽  
Factor Models ◽  
Bifactor Model ◽  
General Factor ◽  
Factor Analyses ◽  
Specific Factors

The revised version of the Beck Depression Inventory (BDI-II) is one of the most frequently applied questionnaires not only in adults, but also in adolescents. To date, attempts to identify a replicable factor structure of the BDI-II have mainly been undertaken in adult populations. Moreover, most of the studies which included minors and were split by gender lacked confirmatory factor analyses and were generally conducted in healthy adolescents. The present study therefore aimed to determine the goodness of fit of various factor models proposed in the literature in an adolescent clinical sample, to evaluate alternative solutions for the factor structure and to explore potential gender differences in factor loadings. The focus was on testing bifactor models and subsequently on calculating bifactor statistical indices to help clarify whether a uni- or a multidimensional construct is more appropriate, and on testing the best-fitting factor model for measurement invariance according to gender. The sample comprised 835 adolescent girls and boys aged 13–18 years in out- and inpatient setting. Several factor models proposed in the literature provided a good fit when applied to the adolescent clinical sample, and differences in goodness of fit were small. Exploratory factor analyses were used to develop and test a bifactor model that consisted of a general factor and two specific factors, termed cognitive and somatic. The bifactor model confirmed the existence of a strong general factor on which all items load, and the bifactor statistical indices suggest that the BDI-II should be seen as a unidimensional scale. Concerning measurement invariance across gender, there were differences in loadings on item 21 (Loss of interest in sex) on the general factor and on items 1 (Sadness), 4 (Loss of pleasure), and 9 (Suicidal Thoughts) on the specific factors. Thus, partial measurement invariance can be assumed and differences are negligible. It can be concluded that the total score of the BDI-II can be used to measure depression severity in adolescent clinical samples.

scholarly journals Factor structure of Raven's Coloured Progressive Matrices

Psico-USF ◽  
2016 ◽  
Vol 21 (2) ◽  
pp. 259-272 ◽  
Author(s):  
Monalisa Muniz ◽  
Cristiano Mauro Assis Gomes ◽  
Sonia Regina Pasian
Keyword(s):  
Standard Deviation ◽  
Factor Structure ◽  
Factor Model ◽  
Specific Factor ◽  
General Factor ◽  
Factor Analyses ◽  
Confirmatory Factor Analyses ◽  
Confirmatory Factor ◽  
Specific Factors ◽  
Three Factor

Abstract This study's objective was to verify the factor structure of Raven's Coloured Progressive Matrices (CPM). The database used included the responses of 1,279 children, 50.2% of which were males with an average age of 8.48 years old and a standard deviation of 1.49 yrs. Confirmatory factor analyses were run to test seven models based on CPM theory and on a Brazilian study addressing the test's structure. The results did not confirm the CPM theoretical proposition concerning the scales but indicated that the test can be interpreted by one general factor and one specific factor or one general factor and three specific factors; both are bi-dimensional models. The three-factor model is, however, more interpretable, suggesting that the factors can be used as a means of screening children's cognitive developmental stage.

scholarly journals Electronic Health Literacy in Swiss-German Parents: Cross-Sectional Study of eHealth Literacy Scale Unidimensionality

10.2196/14492 ◽  
2020 ◽  
Vol 22 (3) ◽  
pp. e14492 ◽  
Author(s):  
Sibylle Juvalta ◽  
Matthew J Kerry ◽  
Rebecca Jaks ◽  
Isabel Baumann ◽  
Julia Dratva
Keyword(s):  
Health Literacy ◽  
Digital Media ◽  
Factor Structure ◽  
Digital Health ◽  
Cross Sectional Study ◽  
General Factor ◽  
Factor Analyses ◽  
Cross Sectional ◽  
Ehealth Literacy ◽  
Swiss German

Background Parents often use digital media to search for information related to their children’s health. As the quantity and quality of digital sources meant specifically for parents expand, parents’ digital health literacy is increasingly important to process the information they retrieve. One of the earliest developed and widely used instruments to assess digital health literacy is the self-reported eHealth Literacy Scale (eHEALS). However, the eHEALS has not been psychometrically validated in a sample of parents. Given the inconsistency of the eHEALS underlying factor structure across previous reports, it is particularly important for validation to occur. Objective This study aimed to determine the factor structure of the German eHEALS measure in a sample of parents by adopting classic and modern psychometric approaches. In particular, this study sought to identify the eHEALS validity as a unidimensional index as well as the viability for potential subscales. Methods A cross-sectional design was used across two purposive sampling frames: online and paper administrations. Responses were collected between January 2018 and May 2018 from 703 Swiss-German parents. In addition to determining the sampling characteristics, we conducted exploratory factor analysis of the eHEALS by considering its ordinal structure using polychoric correlations. This analysis was performed separately for online–based and paper–based responses to examine the general factor strength of the eHEALS as a unidimensional index. Furthermore, item response theory (IRT) analyses were conducted by fitting eHEALS to a bifactor model to further inspect its unidimensionality and subscale viability. Results Parents in both samples were predominantly mothers (622/703, 88.5%), highly educated (538/703, 76.9%), of Swiss nationality (489/703, 71.8%), and living with a partner (692/703, 98.4%). Factor analyses of the eHEALS indicated the presence of a strong general factor across both paper and online samples, and the Wilcoxon rank-sum test indicated that the eHEALS total sum score was not significantly different between the paper and online samples (P=.12). Finally, the IRT analyses indicated negligible multidimensionality, insufficient subscale reliability after accounting for the eHEALS general factor, and a reduced subset of items that could serve as a unidimensional index of the eHEALS across the paper and online samples. Conclusions The German eHEALS evidenced good psychometric properties in a parent-specific study sample. Factor analyses indicated a strong general factor across purposively distinct sample frames (online and paper). IRT analyses validated the eHEALS as a unidimensional index while failing to find support for subscale usage.

European Differences in Self-Perceived Multiple Intelligences

1999 ◽  
Vol 4 (3) ◽  
pp. 131-138 ◽  
Author(s):  
Adrian Furnham ◽  
Tim Rakow ◽  
Ivan Sarmany-Schuller ◽  
Filip De Fruyt
Keyword(s):  
Sex Differences ◽  
Multiple Intelligences ◽  
Factor Structure ◽  
Factor Analyses ◽  
Verbal Iq ◽  
Sex Effects ◽  
Iq Scores ◽  
Culture Differences ◽  
Three Factor

In this study, 140 Belgian, 227 British, and 177 Slovakian students estimated their own multiple IQ scores as well as that of their parents (mother and father) and siblings (first and second brother and sister). Various factor analyses yielded a clear three-factor structure replicating previous studies. A sex × culture ANOVA on self-ratings of three factors that underline the seven intelligences (verbal, numerical, cultural) showed culture and sex effects as well as interactions. As predicted, males rated their own overall IQ, though not that of their parents or siblings, higher than females did. Males also rated their numerical IQ, but not their verbal or cultural IQ, higher than females did. There were few culture differences but many interactions, nearly all caused by Slovakian females, who rated aspects of their own and their fathers' IQ higher than Slovakian males, while the pattern for the Belgians was precisely the opposite. Participants believed their verbal IQ was higher than their numerical IQ and their cultural IQ. Males believed their verbal and numerical IQ score to be fairly similar, though much higher than their cultural IQ, while females believed their verbal IQ the highest, followed by numerical and cultural IQ. Females also believed they were more intelligent than both parents. Overall results showed consistency in the sex differences in ratings across cultures but differences in level of estimated IQ possibly as a result of cultural demands for modesty.

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