scholarly journals Network analysis of empathy items from the Interpersonal Reactivity Index in 1973 young adults

2018 ◽  
Author(s):  
Giovanni Briganti ◽  
Chantal Kempenaers ◽  
Stephanie Braun ◽  
Eiko I Fried ◽  
Paul Linkowski
Keyword(s):  
Young Adults ◽  
Network Analysis ◽  
Partial Correlation ◽  
State Of The Art ◽  
Reactivity Index ◽  
Interpersonal Reactivity Index ◽  
Additional Information ◽  
Node Centrality ◽  
Partial Correlations ◽  
Centrality Score

The aim of this work is to perform a network analysis on the French adaptation of the Interpersonal Reactivity Index (IRI) scale from a large Belgian database and provide additional information for the construct of empathy. We analyze a database of 1973 healthy young adults who were queried on the IRI scale. A regularized partial correlation network is estimated. In the visualization of the model, items are displayed as nodes, edges represent regularized partial correlations between the nodes. Centrality denotes a node's connectedness with other nodes in the network. The spinglass algorithm and the walktrap algorithm are used to identify communities of items, and state-of-the-art stability analyses are carried out. The spinglass algorithm identifies four communities, the walktrap algorithm five communities. Positive edges are found among nodes belonging to the same community as well as among nodes belonging to different communities. Item 14 ("Other people's misfortunes do not usually disturb me a great deal") shows the highest strength centrality score. The network edges and node centrality order are accurately estimated. Network analysis highlights interesting connections between indicators of empathy; how these results impact empathy models must be assessed in further studies.

scholarly journals Network analysis of empathy items from the interpersonal reactivity index in 1973 young adults

2018 ◽  
Vol 265 ◽  
pp. 87-92 ◽  
Author(s):  
Giovanni Briganti ◽  
Chantal Kempenaers ◽  
Stéphanie Braun ◽  
Eiko I. Fried ◽  
Paul Linkowski
Keyword(s):  
Young Adults ◽  
Network Analysis ◽  
Reactivity Index ◽  
Interpersonal Reactivity Index

scholarly journals A Partial Correlation Screening Approach for Controlling the False Positive Rate in Sparse Gaussian Graphical Models

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Ginette Lafit ◽  
Francis Tuerlinckx ◽  
Inez Myin-Germeys ◽  
Eva Ceulemans
Keyword(s):  
Graphical Models ◽  
False Positive ◽  
Partial Correlation ◽  
State Of The Art ◽  
False Positive Rate ◽  
False Positives ◽  
Gaussian Graphical Models ◽  
Undirected Network ◽  
Partial Correlations ◽  
Positive Rate

AbstractGaussian Graphical Models (GGMs) are extensively used in many research areas, such as genomics, proteomics, neuroimaging, and psychology, to study the partial correlation structure of a set of variables. This structure is visualized by drawing an undirected network, in which the variables constitute the nodes and the partial correlations the edges. In many applications, it makes sense to impose sparsity (i.e., some of the partial correlations are forced to zero) as sparsity is theoretically meaningful and/or because it improves the predictive accuracy of the fitted model. However, as we will show by means of extensive simulations, state-of-the-art estimation approaches for imposing sparsity on GGMs, such as the Graphical lasso, ℓ1 regularized nodewise regression, and joint sparse regression, fall short because they often yield too many false positives (i.e., partial correlations that are not properly set to zero). In this paper we present a new estimation approach that allows to control the false positive rate better. Our approach consists of two steps: First, we estimate an undirected network using one of the three state-of-the-art estimation approaches. Second, we try to detect the false positives, by flagging the partial correlations that are smaller in absolute value than a given threshold, which is determined through cross-validation; the flagged correlations are set to zero. Applying this new approach to the same simulated data, shows that it indeed performs better. We also illustrate our approach by using it to estimate (1) a gene regulatory network for breast cancer data, (2) a symptom network of patients with a diagnosis within the nonaffective psychotic spectrum and (3) a symptom network of patients with PTSD.

scholarly journals Metric Goodness and Measurement Invariance of the Italian Brief Version of Interpersonal Reactivity Index: A Study With Young Adults

2021 ◽  
Vol 12 ◽  
Author(s):  
Pierluigi Diotaiuti ◽  
Giuseppe Valente ◽  
Stefania Mancone ◽  
Angela Grambone ◽  
Andrea Chirico
Keyword(s):  
Young Adults ◽  
Measurement Invariance ◽  
Perspective Taking ◽  
Convergent Validity ◽  
Reactivity Index ◽  
Inverse Association ◽  
Validation Process ◽  
Interpersonal Reactivity Index ◽  
Probabilistic Sampling ◽  
Multidimensional Measure

The Interpersonal Reactivity Index (IRI) is a widely used multidimensional measure to assess empathy across four main dimensions: perspective taking (PT) empathic concern (EC) personal distress (PD) fantasy (F). This study aimed to replicate the Italian validation process of the shortened IRI (Interpersonal Reactivity Index) scale in order to confirm its psychometric properties with a sample of young adults. The Gender Measurement Invariance of empathy in this age group was also an objective of the work in order to increase the data on this aspect. A total of 683 Italian university students participated in a non-probabilistic sampling. The 16-item version was confirmed in its four-factor structure but with changes to some items. The model showed good fits with both the CFA and the gender Measurement Invariance. The internal consistency measures were found to be fully satisfactory. Convergent validity was tested by the correlations with the Prosocialness Scale for Adults and The Toronto Alexithymia Scale-20. As hypothesized the measure proved good convergent validity with Prosocialness, i.e., the willingness to assist, help, share, care and empathy with others, and a relevant inverse association with the External Oriented Thinking, characterizing individuals with emotionally poor thinking. This research provided additional evidence for a link between alexithymia and poor empathic abilities in young adults.

Interpersonal Reactivity Index for Couples

2010 ◽  
Author(s):  
Katherine Péloquin ◽  
Marie-France Lafontaine
Keyword(s):  
Reactivity Index ◽  
Interpersonal Reactivity Index

Az SPSI-A hazai adaptálásának eredményei

2017 ◽  
Vol 72 (2) ◽  
pp. 201-229 ◽  
Author(s):  
Kasik László ◽  
Vidákovich Tibor ◽  
Gáspár Csaba ◽  
Tóth Edit
Keyword(s):  
Problem Solving ◽  
Trait Anxiety ◽  
Social Problem ◽  
Social Problem Solving ◽  
Reactivity Index ◽  
State Trait Anxiety Inventory ◽  
Interpersonal Reactivity Index

Kutatásunk célja az SPSI—A (Social Problem Solving Inventory—Adolescent, Frauenknecht és Black, 2010) adaptálása volt 12 és 16 évesek körében (N=540). A kérdőív konvergens és diszkriminatív validitásának vizsgálatához az SPSI—R-t (Social Problem Solving Inventory—Revised, D’Zurilla és mtsai, 2002), a Davis által kidolgozott empátiakérdőívet (Interpersonal Reactivity Index, 1980), valamint a Spielberger- féle vonás - és állapotszorongást mérő kérdőívet (State-Trait Anxiety Inventory for Children, Spielberger és mtsai, 1973) használtuk. Az eredeti kérdőív 10 faktoros, 64 kijelentésből áll. A feltáró és a megerősítő faktorelemzés eredményei alapján a magyar változat — SPSI—A(H) – 54 tételt tartalmaz, melyek 11 faktorba csoportosulnak (az eredeti Gondolatok faktor kijelentései elkülönülnek a Pozitív gondolatok és a Negatív gondolatok faktorba). A kérdőív mind a 12, mind a 16 évesek mintáján jó megbízhatósággal (a Cronbach-α sorrendben 0,81 és 0,83) mér. Az eredmények alapján az SPSI—A(H)-t alkalmasnak tartjuk a problémamegoldással kapcsolatos automatikus gondolatok, a problémamegoldáshoz való érzelmi, gondolati viszonyulás, az elkerülés, a probléma meghatározása, a célmeghatározás, az alternatív megoldási módok keresése, a következmények végiggondolása, illetve a nem megfelelő megoldás esetében a gondolatok, teendők újraszervezése és az utólagos kiértékelés mérésére.

scholarly journals Users roles identification on online crowdsourced Q&A platforms and encyclopedias: a survey

2021 ◽  
Author(s):  
Akrati Saxena ◽  
Harita Reddy
Keyword(s):  
Network Analysis ◽  
Knowledge Sharing ◽  
Informal Learning ◽  
Social Roles ◽  
Online Discussion ◽  
State Of The Art ◽  
Temporal Analysis ◽  
The State ◽  
Open Research ◽  
Research Questions

AbstractOnline informal learning and knowledge-sharing platforms, such as Stack Exchange, Reddit, and Wikipedia have been a great source of learning. Millions of people access these websites to ask questions, answer the questions, view answers, or check facts. However, one interesting question that has always attracted the researchers is if all the users share equally on these portals, and if not then how the contribution varies across users, and how it is distributed? Do different users focus on different kinds of activities and play specific roles? In this work, we present a survey of users’ social roles that have been identified on online discussion and Q&A platforms including Usenet newsgroups, Reddit, Stack Exchange, and MOOC forums, as well as on crowdsourced encyclopedias, such as Wikipedia, and Baidu Baike, where users interact with each other through talk pages. We discuss the state of the art on capturing the variety of users roles through different methods including the construction of user network, analysis of content posted by users, temporal analysis of user activity, posting frequency, and so on. We also discuss the available datasets and APIs to collect the data from these platforms for further research. The survey is concluded with open research questions.

Dichotomization, Partial Correlation, and Conditional Independence

1996 ◽  
Vol 21 (3) ◽  
pp. 264-282 ◽  
Author(s):  
András Vargha ◽  
Tamás Rudas ◽  
Harold D. Delaney ◽  
Scott E. Maxwell
Keyword(s):  
Conditional Independence ◽  
Partial Correlation ◽  
Statistical Significance ◽  
Conventional Wisdom ◽  
Predictor Variables ◽  
Lower Power ◽  
Partial Correlations ◽  
Current Article ◽  
The Difference ◽  
The Relationship

It was recently demonstrated that performing median splits on both of two predictor variables could sometimes result in spurious statistical significance instead of lower power. Not only is the conventional wisdom that dichotomization always lowers power incorrect, but the current article further demonstrates that inflation of apparent effects can also occur in certain cases where only one of two predictor variables is dichotomized. In addition, we show that previously published formulas claiming that correlations are necessarily reduced by bivariate dichotomization are incorrect. While the magnitude of the difference between the correct and incorrect formulas is not great for small or moderate correlations, it is important to correct the misunderstanding of partial correlations that led to the error in the previous derivations. This is done by considering the relationship between partial correlation and conditional independence in the context of dichotomized predictor variables.

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