Understanding Nomophobia: Structural Equation Modeling and Semantic Network Analysis of Smartphone Separation Anxiety

2017 ◽  
Vol 20 (7) ◽  
pp. 419-427 ◽  
Author(s):  
Seunghee Han ◽  
Ki Joon Kim ◽  
Jang Hyun Kim
Keyword(s):  
Structural Equation Modeling ◽  
Network Analysis ◽  
Structural Equation ◽  
Separation Anxiety ◽  
Semantic Network ◽  
Equation Modeling ◽  
Semantic Network Analysis

Burnout–Depression Overlap: Exploratory Structural Equation Modeling Bifactor Analysis and Network Analysis

Assessment ◽  
2020 ◽  
pp. 107319112091109 ◽  
Author(s):  
Jay Verkuilen ◽  
Renzo Bianchi ◽  
Irvin Sam Schonfeld ◽  
Eric Laurent
Keyword(s):  
Structural Equation Modeling ◽  
Network Analysis ◽  
Structural Equation ◽  
Depression Scale ◽  
Equation Modeling ◽  
Anxiety And Depression ◽  
Health Questionnaire ◽  
Hospital Anxiety ◽  
Exploratory Structural Equation Modeling ◽  
Patient Health

Burnout has been viewed as a work-induced condition combining exhaustion, cynicism, and professional inefficacy. Using correlational analyses, an exploratory structural equation modeling bifactor analysis, structural regression analyses, and a network analysis, we examined the claim that burnout should not be mistaken for a depressive syndrome. The study involved 1,258 educational staff members. Burnout was assessed with the Maslach Burnout Inventory–General Survey and depression with the Patient Health Questionnaire–9 and the Hospital Anxiety and Depression Scale. Illegitimate work tasks and work–nonwork interferences were additionally measured. We notably found that (a) on average, exhaustion, cynicism, and professional inefficacy correlated less strongly with each other than with depression; (b) exhaustion―burnout’s core―was more strongly associated with depression than with either cynicism or professional inefficacy; (c) the Patient Health Questionnaire–9 did not correlate more strongly with the Hospital Anxiety and Depression Scale than with exhaustion; (d) exhaustion and depression loaded primarily on a general distress/dysphoria factor in the exploratory structural equation modeling bifactor analysis; (e) on average, burnout and depression were related to job stressors in a similar manner; (f) work–nonwork interferences were strongly linked to distress/dysphoria. Overall, burnout showed no syndromal unity and lacked discriminant validity. Clinicians should systematically assess depressive symptoms in individuals presenting with a complaint of “burnout.”

scholarly journals The JASP Data Library (1st ed.)

2020 ◽  
Author(s):  
Eric-Jan Wagenmakers ◽  
Šimon Kucharský
Keyword(s):  
Factor Analysis ◽  
Structural Equation Modeling ◽  
Network Analysis ◽  
Structural Equation ◽  
Meta Analysis ◽  
Equation Modeling ◽  
Data Library

This is the documentation for the examples contained in the JASP Data Library. The structure of this documentation follows the layout of the JASP ribbon: the first parts deal with Descriptives, T-tests, ANOVA, Regression, Frequencies, and Factor Analysis, whereas the remaining parts concern various JASP modules, namely Meta-Analysis, Network Analysis, and Structural Equation Modeling.

Network interactions among limbic cortices, basal forebrain, and cerebellum differentiate a tone conditioned as a Pavlovian excitor or inhibitor: fluorodeoxyglucose mapping and covariance structural modeling

1994 ◽  
Vol 72 (4) ◽  
pp. 1717-1733 ◽  
Author(s):  
A. R. McIntosh ◽  
F. Gonzalez-Lima
Keyword(s):  
Structural Equation Modeling ◽  
Discriminant Analysis ◽  
Network Analysis ◽  
Basal Forebrain ◽  
Structural Equation ◽  
Brain Regions ◽  
Retrosplenial Cortex ◽  
Equation Modeling ◽  
Regional Activity ◽  
Path Coefficients

1. The objective was to examine how opposite learned behavioral responses to the same physical tone were differentiated by the pattern of interactions between extraauditory neural regions. This was pursued using a new approach combining behavior, neuroimaging, and network analysis to integrate information about differences in regional activity with differences in the covariance relationships between brain areas. 2. A tone was used as either a Pavlovian conditioned excitor or inhibitor. Rats were conditioned with reinforced trials of a conditioned excitor (A+) intermixed with nonreinforced trials of a tone-light compound (AX-). The tone was the excitor (A+) for the tone-excitor group and was the inhibitor (X-) for the tone-inhibitor group. After conditioning, all rats were injected with [14C(U)]2-fluoro-2-deoxyglucose (FDG) and presented with the same tone. 3. FDG autoradiography was used to measure regional activity and to generate interregional correlations of activity resulting from the presentation of the tone. A stepwise discriminant analysis was used to select brain regions that differentiated the excitor from the inhibitor effects. 4. Network analysis consisted of constructing an anatomic model of the brain regions, selected by the discriminant analysis, linking the regions with their known anatomical connections. Then, functional models for the tone-excitor and -inhibitor groups were constructed using structural equation modeling. Correlations of activity between regions were decomposed to calculate numerical weights, or path coefficients, for each anatomic path. These path coefficients were used to compare the interactions for the tone-excitor and -inhibitor models. 5. Regional differences in FDG uptake were found in the sulcal frontal cortex (SFC), lateral septum (LS), medial septum/diagonal band (MS/DB), retrosplenial cortex (RS), and dentate-interpositus nuclei of the cerebellum (DEN). Discriminant analysis selected three other regions that significantly discriminated the tone-excitor and -inhibitor groups: perirhinal cortex (PRh), nucleus accumbens (ACB), and the anteroventral nucleus of the thalamus (AVN). 6. Structural equation modeling identified two functional circuits that differentiated the groups. One involved the basal forebrain regions (LS, MS/DB, ACB) and the other limbic thalamocortical structures (SFC, RS, PRh, AVN). Differences in the interactions within these circuits were mainly in sign of the covariance relationships between regions, from positive for the tone-excitor model to negative path coefficients for the tone-inhibitor model. The path coefficient between the basal forebrain circuit and the limbic thalamocortical circuit showed the largest magnitude difference. This quantitative difference was mediated by a path from the MS/DB to PRh.(ABSTRACT TRUNCATED AT 400 WORDS)

Testing the Assumption of Uncorrelated Errors for Short Scales by Means of Structural Equation Modeling

2014 ◽  
Vol 35 (4) ◽  
pp. 201-211 ◽  
Author(s):  
André Beauducel ◽  
Anja Leue
Keyword(s):  
Structural Equation Modeling ◽  
Negative Correlation ◽  
Structural Equation ◽  
Error Score ◽  
Classical Test Theory ◽  
Test Theory ◽  
Equation Modeling ◽  
Eysenck Personality Questionnaire ◽  
Personality Questionnaire ◽  
True Score

It is shown that a minimal assumption should be added to the assumptions of Classical Test Theory (CTT) in order to have positive inter-item correlations, which are regarded as a basis for the aggregation of items. Moreover, it is shown that the assumption of zero correlations between the error score estimates is substantially violated in the population of individuals when the number of items is small. Instead, a negative correlation between error score estimates occurs. The reason for the negative correlation is that the error score estimates for different items of a scale are based on insufficient true score estimates when the number of items is small. A test of the assumption of uncorrelated error score estimates by means of structural equation modeling (SEM) is proposed that takes this effect into account. The SEM-based procedure is demonstrated by means of empirical examples based on the Edinburgh Handedness Inventory and the Eysenck Personality Questionnaire-Revised.

The Measurement Invariance of the Short Dark Triad

2020 ◽  
Vol 41 (4) ◽  
pp. 207-218
Author(s):  
Mihaela Grigoraș ◽  
Andreea Butucescu ◽  
Amalia Miulescu ◽  
Cristian Opariuc-Dan ◽  
Dragoș Iliescu
Keyword(s):  
Structural Equation Modeling ◽  
Item Response ◽  
Structural Equation ◽  
Dark Triad ◽  
Theory And Practice ◽  
Equation Modeling ◽  
Scale Level ◽  
High Stake ◽  
Differential Functioning ◽  
Item Functioning

Abstract. Given the fact that most of the dark personality measures are developed based on data collected in low-stake settings, the present study addresses the appropriateness of their use in high-stake contexts. Specifically, we examined item- and scale-level differential functioning of the Short Dark Triad (SD3; Paulhus & Jones, 2011 ) measure across testing contexts. The Short Dark Triad was administered to applicant ( N = 457) and non-applicant ( N = 592) samples. Item- and scale-level invariances were tested using an Item Response Theory (IRT)-based approach and a Structural Equation Modeling (SEM) approach, respectively. Results show that more than half of the SD3 items were flagged for Differential Item Functioning (DIF), and Exploratory Structural Equation Modeling (ESEM) results supported configural, but not metric invariance. Implications for theory and practice are discussed.

Childhood Intelligence Predicts Adult Trait Openness

2016 ◽  
Vol 37 (2) ◽  
pp. 105-111 ◽  
Author(s):  
Adrian Furnham ◽  
Helen Cheng
Keyword(s):  
Structural Equation Modeling ◽  
Structural Equation ◽  
Social Background ◽  
Study Data ◽  
Equation Modeling ◽  
Direct Effects ◽  
Data Set ◽  
National Child Development Study ◽  
Nationally Representative ◽  
The Uk

Abstract. This study used a longitudinal data set of 5,672 adults followed for 50 years to determine the factors that influence adult trait Openness-to-Experience. In a large, nationally representative sample in the UK (the National Child Development Study), data were collected at birth, in childhood (age 11), adolescence (age 16), and adulthood (ages 33, 42, and 50) to examine the effects of family social background, childhood intelligence, school motivation during adolescence, education, and occupation on the personality trait Openness assessed at age 50 years. Structural equation modeling showed that parental social status, childhood intelligence, school motivation, education, and occupation all had modest, but direct, effects on trait Openness, among which childhood intelligence was the strongest predictor. Gender was not significantly associated with trait Openness. Limitations and implications of the study are discussed.

Celebrity Worship Among University Students in Malaysia

2011 ◽  
Vol 16 (4) ◽  
pp. 334-342 ◽  
Author(s):  
Viren Swami ◽  
Tomas Chamorro-Premuzic ◽  
Khairul Mastor ◽  
Fatin Hazwani Siran ◽  
Mohammad Mohsein Mohammad Said ◽  
...  
Keyword(s):  
Factor Analysis ◽  
Structural Equation Modeling ◽  
Structural Equation ◽  
Attitude Scale ◽  
Equation Modeling ◽  
Future Research ◽  
The West ◽  
Factor Solution ◽  
Movie Stars ◽  
Three Factor

The present study examined conceptual issues surrounding celebrity worship in a Malay-speaking population. In total, 512 Malay and 269 Chinese participants from Malaysia indicated who their favorite celebrity was and completed the Celebrity Attitude Scale (CAS) as well as a range of demographic items. Results showed that the majority of Malay and Chinese participants selected pop stars and movie stars as their favourite celebrities, mirroring findings in Western settings. In addition, exploratory factor analysis revealed a three-factor solution of the CAS that was consistent with previous studies conducted in the West. Structural equation modeling further revealed that participant’s age was negatively associated with celebrity worship and that self-rated attractiveness was positively associated with celebrity worship. Overall, the present results suggest that celebrity worship in Malaysia may be driven by market and media forces, and future research may well be guided by use of the CAS.

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