Network Analysis on Attitudes

Dalege, Jonas; Borsboom, Denny; Harreveld, Frenk van; Maas, Han L. J. van der

doi:10.1177/1948550617709827

Cited by 172 publications

(152 citation statements)

References 41 publications

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“…Previous evidence showed that age, gender, and employment status might influence hopelessness (Greene, 1981;Haatainen, Tanskanen, Kylma, Antikainen, et al, 2003;Haatainen, Tanskanen, Kylma, Honkalampi, et al, 2003). Hence, in line with Dalege, Borsboom, van Harreveld, and van der Maas (2017), the network model and the local structure indexes were re-estimated, after controlling for age, gender, and employment status.…”

Section: Covariating Age Gender and Employment Statusmentioning

confidence: 99%

Hopelessness: A Network Analysis

Marchetti

2018

Cogn Ther Res

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Hopelessness is a complex phenomenon with important clinical consequences, such as depression and suicidality. Despite its major impact on mental health, little is known about the structure of hopelessness. In this study, hopelessness was investigated in a large community sample (n = 1985), recruited to be highly representative of general population in Germany. In the context of network analysis, state-of-the-art techniques were adopted (i) to investigate which thoughts and beliefs (nodes) are the most central ones and (ii) to shed light on the specific associations (edges) among them. Stability and accuracy were also checked to ensure trustworthiness of the findings. The analyses revealed that expecting more negative than positive future events and having important goals blocked along with feelings of giving-up were the most central elements of hopelessness. Moreover, being unable to imagine the future and perceiving it as vague and uncertain were both coupled with anticipating a dark future.Theoretical and clinical consequences of this study were discussed.

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Section: Covariating Age Gender and Employment Statusmentioning

confidence: 99%

Hopelessness: A Network Analysis

Marchetti

2018

Cogn Ther Res

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“…In addition, we estimated centrality of nodes using three different centrality measures (Opsahl, Agneessens, & Skvoretz, ; see Figure ), which reveal the structural importance of the different nodes. The most easily interpreted is centrality strength, which represents the direct influence a given node has on the network (Dalege, Borsboom, van Harreveld, & van der Maas, ), i.e., a strength‐central node has influence on many other nodes. Closeness and betweenness both depend on the concept of shortest path lengths (Dijkstra, ) and closeness represents how likely it is that information from a node spread through the whole network directly or indirectly.…”

Section: Methodsmentioning

confidence: 99%

Dimensionality of oppositional defiant disorder

Hukkelberg

Ogden

2017

Child Adoles Ment Health

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Background: The present study examined dimensionality of oppositional defiant disorder (ODD) using 10 alternative items using network analysis and confirmatory factor analysis. Methods: The sample constituted 551 Norwegian children aged 2-12 and their parents. We used network analysis to investigate the connections between different symptoms. Next, we analysed data using traditional confirmatory factor methods, including the more recently proposed bifactor approach. Results: The bifactor model, with a strong general factor and three specific factors, provided the best model fit. Omega values did, however, reveal that only the general and the specific hurtful factor had satisfactory reliability. Network analysis showed that symptoms in general were positively connected within the ODD network. Strong connections between several symptoms within the irritable and hurtful cluster emerged, whereas some symptoms of the headstrong cluster seem to function as bridge nodes between the irritable and hurtful symptom clusters. Conclusions: The findings support a bifactor model of ODD indicators, but omegas only gave support to the use of a general latent factor, and one specific factor. Network analysis did, however, provide some additional and interesting findings, revealing clusters of strongly connected symptoms and central bridge node symptoms. Implications of the results are discussed. Key Practitioner Message• Oppositional Defiant Disorder (ODD) is a leading cause of referral for youth mental health problems. • Findings organize ODD symptoms into three dimensions reflecting irritable, headstrong, and hurtful behavior.• The present study evaluated ten alternative items reflecting ODD, using explorative network analysis and confirmatory factor analysis.• Network analysis represents an alternative to the latent reflective approach, as it assumes that ODD constitutes a network of symptoms that associate and interact with each other.• Factor analysis showed that the bifactor model provided best fit to the data, but omega reliabilities only supported the use of a general ODD factor, not the distinct factors.• Network analysis revealed clusters of symptoms reflecting irritability and hurtful, but to a lesser extent headstrong.

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“…Nodes represent the variables of interest in a study (i.e., scale items) and edges connect the nodes into a superstructure via their pairwise interactions. Once a network is formed, network analysis gives us the power to observe complex relationships between variables, but also to study the most important or least important nodes within a system (Borsboom et al, 2011; see also Costantini et al, 2019;Dalege et al, 2017;Epskamp et al, 2018). We leveraged network analysis to provide a complimentary investigation of the MFQ-r and its structure, owing to the borderline acceptable levels of some model fit statistics.…”

Section: Parallel Network Analysis Of the Revised Mfqmentioning

confidence: 99%

Reanalyzing the factor structure of the Moral Foundations Questionnaire

Harper¹,

Rhodes²

2020

Preprint

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The moral foundations theory (MFT) is an influential multifactorial model that posits how decision-making in the moral context originates from a set of six intuitive moral foundations: care, fairness, authority, loyalty, purity, and liberty. The established measure of these foundations – the Moral Foundations Questionnaire (MFQ) – has been used extensively in a range of empirical projects. However, recent analyses of its factor structure and the internal consistency of the each of the foundation clusters have called its validity into question. In this paper, data from a large sample of British voters (N = 428) was used to re-examine the component structure of the MFQ. As opposed to a six-component structure, only three meaningful clusters emerged: traditionalism, compassion, and liberty. Concurrent validity was established via correlations with measures of ‘social change’ and ‘systemic inequality’ insecurities, while significant differences on each of the three components of the revised MFQ (MFQ-r) were observed between the voters of different political parties. Implications for moral foundations theory and its measurement are discussed.

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Network Analysis on Attitudes

Cited by 172 publications

References 41 publications

Hopelessness: A Network Analysis

Hopelessness: A Network Analysis

Dimensionality of oppositional defiant disorder

Reanalyzing the factor structure of the Moral Foundations Questionnaire

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