A network analysis of the General Health questionnaire
- Authors: Van Zyl, Casper J J
- Date: 2020
- Subjects: Common cause , Confirmatory factor analysis , General Health Questionnai
- Language: English
- Type: Article
- Identifier: http://hdl.handle.net/10210/473537 , uj:42653 , Van Zyl, C.J.J. 2020. A network analysis of the General Health Questionnaire.
- Description: Abstract: The General Health Questionnaire-28 is a well-known symptom-based rating scale of mental health. Several studies have investigated its latent structure using confirmatory factor analysis. This study questions this approach on several substantive points, most notably the inability for symptoms to interact using confirmatory factor analysis, and argues for the use of network analysis instead. Network results demonstrate the method’s utility to improve our understanding of the rating scales’ symptom structure. Insights include a much richer understanding of comorbidity on the General Health Questionnaire-28 and the identification of particularly salient symptoms affecting the network. It yields substantive information of interest to researchers and practitioners alike.
- Full Text:
- Authors: Van Zyl, Casper J J
- Date: 2020
- Subjects: Common cause , Confirmatory factor analysis , General Health Questionnai
- Language: English
- Type: Article
- Identifier: http://hdl.handle.net/10210/473537 , uj:42653 , Van Zyl, C.J.J. 2020. A network analysis of the General Health Questionnaire.
- Description: Abstract: The General Health Questionnaire-28 is a well-known symptom-based rating scale of mental health. Several studies have investigated its latent structure using confirmatory factor analysis. This study questions this approach on several substantive points, most notably the inability for symptoms to interact using confirmatory factor analysis, and argues for the use of network analysis instead. Network results demonstrate the method’s utility to improve our understanding of the rating scales’ symptom structure. Insights include a much richer understanding of comorbidity on the General Health Questionnaire-28 and the identification of particularly salient symptoms affecting the network. It yields substantive information of interest to researchers and practitioners alike.
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Attitude to ambiguity as a predictor of analytic thinking
- Authors: Van Zyl, Casper J J
- Date: 2020
- Subjects: Analytic thinking , Attitude to ambiguity , Belief bias
- Language: English
- Type: Article
- Identifier: http://hdl.handle.net/10210/473529 , uj:42652 , Citation: Van Zyl, C.J.J. 2020. Attitude to ambiguity as a predictor of analytic thinking.
- Description: Abstract: Thinking dispositions are considered important predictors of analytic thinking. While several thinking dispositions have been found to predict responses on a range of analytic thinking tasks, this field is arguably underdeveloped. There are likely many relevant dispositional variables associated with analytic thinking that remains to be explored. This study examines one such dispositional variable, namely, attitude to ambiguity. The disposition is implied in the literature given that internal conflict – likely with associated ambiguity – is typically experienced in cognitive tasks used to study thinking and reasoning. In this article, the association between attitude to ambiguity and analytic thinking is empirically examined using Bayesian methods. A total of 313 adults (mean age = 29.31, SD = 12.19) completed the Multidimensional Attitude Toward Ambiguity (MAAS) scale, along with the Cognitive Reflection Test and a syllogism-based measure of belief bias. Results found one component of the MAAS scale, Moral Absolutism, to be a robust predictor of scores on both the Cognitive Reflection Test and the measure of belief bias.
- Full Text:
- Authors: Van Zyl, Casper J J
- Date: 2020
- Subjects: Analytic thinking , Attitude to ambiguity , Belief bias
- Language: English
- Type: Article
- Identifier: http://hdl.handle.net/10210/473529 , uj:42652 , Citation: Van Zyl, C.J.J. 2020. Attitude to ambiguity as a predictor of analytic thinking.
- Description: Abstract: Thinking dispositions are considered important predictors of analytic thinking. While several thinking dispositions have been found to predict responses on a range of analytic thinking tasks, this field is arguably underdeveloped. There are likely many relevant dispositional variables associated with analytic thinking that remains to be explored. This study examines one such dispositional variable, namely, attitude to ambiguity. The disposition is implied in the literature given that internal conflict – likely with associated ambiguity – is typically experienced in cognitive tasks used to study thinking and reasoning. In this article, the association between attitude to ambiguity and analytic thinking is empirically examined using Bayesian methods. A total of 313 adults (mean age = 29.31, SD = 12.19) completed the Multidimensional Attitude Toward Ambiguity (MAAS) scale, along with the Cognitive Reflection Test and a syllogism-based measure of belief bias. Results found one component of the MAAS scale, Moral Absolutism, to be a robust predictor of scores on both the Cognitive Reflection Test and the measure of belief bias.
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The five factor model and infidelity : beyond the broad domains
- Authors: Van Zyl, Casper J J
- Date: 2020
- Subjects: Five factor model , Personality , Infidelity
- Language: English
- Type: Article
- Identifier: http://hdl.handle.net/10210/473542 , uj:42654 , Citation: Van Zyl, C.J.J. 2020. The five factor model and infidelity : beyond the broad domains.
- Description: Abstract: Several studies have explored the association between personality and infidelity, but our understanding of this relationship is arguably underdeveloped. The fact that most research only examined domain-level effects may have contributed to the situation, as facet-level and item- level information have not sufficiently been taken into consideration. This paper argues that it is an unwarranted assumption that domain-level associations reveal all there is to know about the relationship between personality and infidelity, and proceeds to examine this claim. The present study investigates the association between personality and infidelity but goes beyond the Big Five domains to examine facet and item-level associations in a sample of 685 participants. Bayesian logistic modeling with comprehensive indicators of uncertainty are provided for all models predicting infidelity. Results suggest that two facets in particular are associated with infidelity and that facet and item models contains additional predictive information compared to the broad domains. Findings further suggest that facets and items provide more nuanced information than can be gleaned from domain-level effects, which in turn, could advance our understanding of personality and its association with infidelity.
- Full Text:
- Authors: Van Zyl, Casper J J
- Date: 2020
- Subjects: Five factor model , Personality , Infidelity
- Language: English
- Type: Article
- Identifier: http://hdl.handle.net/10210/473542 , uj:42654 , Citation: Van Zyl, C.J.J. 2020. The five factor model and infidelity : beyond the broad domains.
- Description: Abstract: Several studies have explored the association between personality and infidelity, but our understanding of this relationship is arguably underdeveloped. The fact that most research only examined domain-level effects may have contributed to the situation, as facet-level and item- level information have not sufficiently been taken into consideration. This paper argues that it is an unwarranted assumption that domain-level associations reveal all there is to know about the relationship between personality and infidelity, and proceeds to examine this claim. The present study investigates the association between personality and infidelity but goes beyond the Big Five domains to examine facet and item-level associations in a sample of 685 participants. Bayesian logistic modeling with comprehensive indicators of uncertainty are provided for all models predicting infidelity. Results suggest that two facets in particular are associated with infidelity and that facet and item models contains additional predictive information compared to the broad domains. Findings further suggest that facets and items provide more nuanced information than can be gleaned from domain-level effects, which in turn, could advance our understanding of personality and its association with infidelity.
- Full Text:
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