scholarly journals Visual art inspired by climate change—An analysis of audience reactions to 37 artworks presented during 21st UN climate summit in Paris

PLoS ONE ◽  
2021 ◽  
Vol 16 (2) ◽  
pp. e0247331
Author(s):  
Christian Andreas Klöckner ◽  
Laura K. Sommer
Keyword(s):  
Climate Change ◽  
Cognitive Processing ◽  
Structural Equation ◽  
Environmental Attitudes ◽  
Policy Support ◽  
Multilevel Structural Equation Modeling ◽  
Equation Modeling ◽  
Climate Policies ◽  
Emotional Activation ◽  
First Impression

This paper suggests and tests a psychological model of environmental art perception and subsequent support for climate change policies. The model is based on findings from art perception and environmental psychology, which indicate that the response of the viewer to the artwork is (1) first an emotional reaction, which can be positive and/or negative. The emotional activation leads to (2) evaluation of the perceived quality of the artwork. This forms the first impression of the artwork the viewer gets, which then triggers (3) reflections on the artwork that are finally related to support for climate policies. The model test uses data collected at the ArtCOP21 that accompanied the 21st UN climate summit in Paris. At 37 connected events, the research team collected 883 audience responses with a brief quantitative paper-pencil questionnaire. The data were analyzed using a multilevel-structural equation modeling approach. Results support the suggested theoretical model. Moreover, the effect of reflections on the artwork on support for climate policies is moderated by environmental attitudes, meaning the lower the environmental attitudes, the higher the effect of reflections on policy support. Finally, artwork features like color, size, displaying something personal, etc., could be identified that had a significant relation to differences on the artwork level regarding the first impression of the artwork and the reflections elicited. The study shows that being confronted with climate change-related artwork relates at least in the short run to increased climate policy support, which is mostly channeled through an emotional activation with following cognitive processing. Features of the artwork relate to how strongly and which emotions are activated.

Meta-Accuracy and Perceived Reciprocity From the Perception-Meta-Perception Social Relations Model

2019 ◽  
Vol 50 (1) ◽  
pp. 24-37
Author(s):  
Ben Porter ◽  
Camilla S. Øverup ◽  
Julie A. Brunson ◽  
Paras D. Mehta
Keyword(s):  
Structural Equation Modeling ◽  
Social Relations ◽  
Latent Variables ◽  
Structural Equation ◽  
Multilevel Structural Equation Modeling ◽  
Equation Modeling ◽  
Complete Understanding ◽  
Social Relations Model ◽  
Flexible Framework ◽  
Multilevel Structural Equation

Abstract. Meta-accuracy and perceptions of reciprocity can be measured by covariances between latent variables in two social relations models examining perception and meta-perception. We propose a single unified model called the Perception-Meta-Perception Social Relations Model (PM-SRM). This model simultaneously estimates all possible parameters to provide a more complete understanding of the relationships between perception and meta-perception. We describe the components of the PM-SRM and present two pedagogical examples with code, openly available on https://osf.io/4ag5m . Using a new package in R (xxM), we estimated the model using multilevel structural equation modeling which provides an approachable and flexible framework for evaluating the PM-SRM. Further, we discuss possible expansions to the PM-SRM which can explore novel and exciting hypotheses.

Impulsivity, Affect, and Stress in Daily Life: Examining a Cascade Model of Urgency

2019 ◽  
Author(s):  
Brinkley M. Sharpe ◽  
Leonard Simms ◽  
Aidan G.C. Wright
Keyword(s):  
Negative Affect ◽  
Structural Equation ◽  
Psychiatric Patients ◽  
Cascade Model ◽  
Multilevel Structural Equation Modeling ◽  
Equation Modeling ◽  
Daily Stress ◽  
Daily Diary Study ◽  
Daily Affect ◽  
Multilevel Structural Equation

Using multilevel structural equation modeling, we examined within- and between-person predictors of daily impulsivity, with a particular focus on testing a cascade model of affect and daily stress in a 100-day daily diary study of 101 psychiatric patients with personality disorder diagnoses. On average (i.e., fixed effect), within-person increases in daily stress were associated with increased daily impulsivity, both independently and as accounted for by positive associations with increased negative and positive affect. Higher Personality Inventory for DSM-5 (PID-5) Impulsivity scores were associated with amplified within-person links between impulsivity and daily stress and negative affect, but not the links between daily stress and either positive or negative affect. The results of this cascade model are consistent with the hypothesized link between daily affect and stress and daily impulsivity while providing further evidence for the validity of the PID-5 Impulsivity scale and its ability to predict daily impulsivity above and beyond fluctuations in affect and stress.

Comparing respondents who passed versus failed an Instructional Manipulation Check: A case study about support for climate change policies

2021 ◽  
Vol 63 (4) ◽  
pp. 408-415
Author(s):  
Maria Rubio Juan ◽  
Melanie Revilla
Keyword(s):  
Climate Change ◽  
External Validity ◽  
Structural Equation ◽  
Online Survey ◽  
Equation Modeling ◽  
Manipulation Check ◽  
Climate Change Policies ◽  
Instructional Manipulation ◽  
Using Data

The presence of satisficers among survey respondents threatens survey data quality. To identify such respondents, Oppenheimer et al. developed the Instructional Manipulation Check (IMC), which has been used as a tool to exclude observations from the analyses. However, this practice has raised concerns regarding its effects on the external validity and the substantive conclusions of studies excluding respondents who fail an IMC. Thus, more research on the differences between respondents who pass versus fail an IMC regarding sociodemographic and attitudinal variables is needed. This study compares respondents who passed versus failed an IMC both for descriptive and causal analyses based on structural equation modeling (SEM) using data from an online survey implemented in Spain in 2019. These data were analyzed by Rubio Juan and Revilla without taking into account the results of the IMC. We find that those who passed the IMC do differ significantly from those who failed for two sociodemographic and five attitudinal variables, out of 18 variables compared. Moreover, in terms of substantive conclusions, differences between those who passed and failed the IMC vary depending on the specific variables under study.

The Role of an Empowering Motivational Climate on Pupils’ Concentration and Distraction in Physical Education

2021 ◽  
pp. 1-11
Author(s):  
Maxime Mastagli ◽  
Aurélie Van Hoye ◽  
Jean-Philippe Hainaut ◽  
Benoît Bolmont
Keyword(s):  
Physical Education ◽  
Negative Affect ◽  
Structural Equation ◽  
Psychological Needs ◽  
Motivational Climate ◽  
Need Satisfaction ◽  
Basic Psychological Needs ◽  
Multilevel Structural Equation Modeling ◽  
Equation Modeling ◽  
Positive And Negative Affect

Purpose: The present study investigated the relationship between an empowering motivational climate and pupils’ concentration and distraction in physical education, mediated by basic psychological needs satisfaction and by positive and negative affect. Method: The participants were 425 French pupils (Mage = 15.36, SDage = 0.82) from 21 high schools, who filled in a questionnaire regarding the study variables. This cross-sectional study used multilevel structural equation modeling to examine the hypothesized relationships. Results: Good fit indices were found in the data from the theoretical model. An empowering motivational climate was found to be related to concentration. Competence need satisfaction was related to concentration and distraction. This association was mediated by positive and negative affect, which in turn was related to concentration and distraction. Conclusion: Teachers can improve pupils’ concentration and positive affect and reduce distraction and negative affect by supporting an empowering motivational climate and fostering competence need satisfaction.

scholarly journals Applying the Theory of Planned Behavior to Examine Pro-Environmental Behavior: The Moderating Effect of COVID-19 Beliefs

2020 ◽  
Vol 12 (24) ◽  
pp. 10556
Author(s):  
Caterina Lucarelli ◽  
Camilla Mazzoli ◽  
Sabrina Severini
Keyword(s):  
Climate Change ◽  
Theory Of Planned Behavior ◽  
Least Squares ◽  
Partial Least Squares ◽  
Planned Behavior ◽  
Structural Equation ◽  
Environmental Behavior ◽  
Group Analysis ◽  
Policy Implications ◽  
Equation Modeling

The COVID-19 pandemic and climate change issues present evident interdependencies which justify the spread of connected beliefs. We examine possible changes in individuals’ pro-environmental behavior in light of this pandemic, using the Theory of Planned Behavior (TPB) framework. A questionnaire survey was submitted to the same sample of individuals, before and during the pandemic. Our evidence, based on Partial Least Squares Structural Equation Modeling (PLS-SEM), shows that the COVID-19 pandemic has not led to a weakening in TPB construct relationships, or in related Pro-Environmental Behavior (PEB). Conversely, through our Partial Least Squares-Multi-Group Analysis (PLS-MGA), we show that individuals with greater awareness of interdependencies between the COVID-19 and climate change exhibit both higher Intention and reinforced Pro-Environmental Behaviors. This finding reveals interesting policy implications in terms of innovative behavioral drivers that should be employed to steer public support towards climate-oriented initiatives.

scholarly journals Analyzing Organizational Growth in Repeated Cross-Sectional Designs Using Multilevel Structural Equation Modeling

Methodology ◽  
2017 ◽  
Vol 13 (3) ◽  
pp. 83-97 ◽  
Author(s):  
Jan Hochweber ◽  
Johannes Hartig
Keyword(s):  
Structural Equation Modeling ◽  
Growth Curve ◽  
Cross Sections ◽  
Structural Equation ◽  
Organizational Level ◽  
Multilevel Structural Equation Modeling ◽  
Equation Modeling ◽  
Organizational Growth ◽  
Multilevel Structural Equation ◽  
Level Variable

Abstract. In repeated cross-sections of organizations, different individuals are sampled from the same set of organizations at each time point of measurement. As a result, common longitudinal data analysis methods (e.g., latent growth curve models) cannot be applied in the usual way. In this contribution, a multilevel structural equation modeling approach to analyze data from repeated cross-sections is presented. Results from a simulation study are reported which aimed at obtaining guidelines on appropriate sample sizes. We focused on a situation where linear growth occurs at the organizational level, and organizational growth is predicted by a single organizational level variable. The power to identify an effect of this organizational level variable was moderately to strongly positively related to number of measurement occasions, number of groups, group size, intraclass correlation, effect size, and growth curve reliability. The Type I error rate was close to the nominal alpha level under all conditions.

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