Rodrigo Landabur

Rodrigo Landabur
Universidad de Atacama

MS, PhD in Psychology

About

15
Publications
1,622
Reads
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24
Citations
Citations since 2016
12 Research Items
20 Citations
2016201720182019202020212022024681012
2016201720182019202020212022024681012
2016201720182019202020212022024681012
2016201720182019202020212022024681012
Introduction
Dr. Rodrigo Landabur is a researcher from University of Atacama with training in social and legal psychology. He is interested in predictors of prosocial and antisocial behavior, group relations, legal and forensic psychology. His current projects are associated to identity fusion and motivation for prosocial behavior.
Additional affiliations
June 2021 - present
Universidad de Atacama
Position
  • Investigador
April 2020 - December 2020
University of Chile
Position
  • Laboratory Assistant
July 2016 - February 2020
University of Chile
Position
  • Professor (Assistant)
Education
September 2011 - February 2013
Universidad Autónoma de Madrid
Field of study
  • Forensic sciences

Publications

Publications (15)
Article
Full-text available
La fusión de identidad consiste en un sentimiento de unión con un grupo, en el que el individuo experimenta una mezcla entre su identidad personal y la social; y es un buen predictor de la conducta extrema progrupo. El presente estudio analizó la estructura factorial de la Escala verbal de fusión de identidad elaborada por Gómez et al. (2011), en u...
Article
Full-text available
Migration processes can often trigger negative interactions with the context, generating problems in both the physical and mental health of migrants, which have an impact on both their well-being and their quality of life. In this framework, the research aimed to assess the mediating effect of ethnic identity and collective self-esteem on the inver...
Article
Identity fusion with a group, a feeling of connection with it, is a good predictor of extreme pro‐group behavior, an action to favor or protect the group, including self‐sacrifice. Relational ties and personal distress (self‐oriented emotional reaction; e.g., anxiety, distress) toward ingroup members in need have been evaluated separately as mediat...
Chapter
This entry reviews the main explanations of rescue behavior and describe examples in different animals.
Article
As ordinary citizens increasingly moderate online forums, blogs, and their own social media feeds, a new type of censoring has emerged wherein people selectively remove opposing political viewpoints from online contexts. In three studies of behavior on putative online forums, supporters of a political cause (e.g., abortion or gun rights) preferenti...
Chapter
This chapter analyzes the evolutionary explanations for main types of helping behavior: altruism and cooperation. For altruism, we review the explanation of traits selection at group level.
Preprint
As ordinary citizens increasingly moderate online forums, blogs, and their own social media feeds, a new type of censoring has emerged wherein people selectively remove opposing political viewpoints from online contexts. In three studies of behavior on putative online forums, supporters of a political cause (e.g., abortion or gun rights) preferenti...
Article
Full-text available
Cases of homicidal children are scarce, but they have great social and legislative impact, leading to the study of risk and protector factors of early criminal activity. Given the only record in Chile of a homicidal child, the objective of this study was to the individual and contextual risk factors associated with such homicidal behavior of a chil...
Technical Report
Full-text available
El objetivo general del estudio es proponer un modelo para la construcción de una Batería de instrumentos de Evaluación para el Modelo de Intervención del Servicio Nacional de Reinserción Social Juvenil, analizando los escenarios técnicos posibles en relación a la realidad nacional.

Questions

Question (1)
Question
Imagine a regression with 3 predictors and one dependent variable and sample size over 400. Only one predictor has a positive significant effect, p value equals to .02 aprox. R-squared is low (less than .03) and the R-squared IC 95% includes negative values: I have read that this means my model has worse fit than a horizontal line. Therefore, how to interpret this result? If my model is poor, how can I explain the significant effect of one predictor?

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