scholarly journals Determinants of COVID-19 Vaccine Hesitancy in Portuguese-Speaking Countries: A Structural Equations Modeling Approach

Vaccines ◽  
2021 ◽  
Vol 9 (10) ◽  
pp. 1167
Author(s):  
Álvaro Francisco Lopes de Sousa ◽  
Jules Ramon Brito Teixeira ◽  
Iracema Lua ◽  
Fernanda de Oliveira Souza ◽  
Andrêa Jacqueline Fortes Ferreira ◽  
...  
Keyword(s):  
Factor Analysis ◽  
Structural Equation ◽  
Structural Equation Models ◽  
Structural Equations ◽  
Vaccine Hesitancy ◽  
Cognitive Vulnerabilities ◽  
Measurement Models ◽  
Validated Questionnaire ◽  
Conspiracy Beliefs ◽  
Vaccination Campaigns

COVID-19 vaccine hesitancy (VH) has caused concerns due to the possible fluctuations that may occur directly impacting the control of the pandemic. In this study, we aimed to estimate the prevalence and factors associated with COVID-19 VH in Portuguese-speaking countries. We developed a web survey (N:6,843) using an online, structured, and validated questionnaire. We used Measurement Models, Exploratory Factor Analysis, Exploratory Structural Equation Models, and Confirmatory Factor Analysis for the data analysis. The overall prevalence of COVID-19 VH in Portuguese-speaking countries was 21.1%. showed a statistically significant direct effect for VH: vaccine-related conspiracy beliefs (VB) (β = 0.886), perceived stress (PS) (β = 0.313), COVID-19 Misinformation (MIS) (β = 0.259) and individual responses to COVID-19 (CIR) (β = −0.122). The effect of MIS and CIR for VH was greater among men and of PS and VB among women; the effect of PS was greater among the youngest and of VB and CIR among the oldest. No discrepant differences were identified in the analyzed education strata. In conclusion, we found that conspiracy beliefs related to the vaccine strongly influence the decision to hesitate (not to take or to delay the vaccine). Specific characteristics related to gender, age group, social and cognitive vulnerabilities, added to the knowledge acquired, poorly substantiated and/or misrepresented about the COVID-19 vaccine, need to be considered in the planning of vaccination campaigns. It is necessary to respond in a timely, fast, and accurate manner to the challenges posed by vaccine hesitancy.

scholarly journals The Mediating Roles of Medical Mistrust, Knowledge, Confidence and Complacency of Vaccines in the Pathways from Conspiracy Beliefs to Vaccine Hesitancy

Vaccines ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 1342
Author(s):  
Xiaoning Zhang ◽  
Yuqing Guo ◽  
Qiong Zhou ◽  
Zaixiang Tan ◽  
Junli Cao
Keyword(s):  
Structural Equation ◽  
Model Fit ◽  
Vaccine Hesitancy ◽  
Equation Modeling ◽  
Medical Mistrust ◽  
Measurement Models ◽  
Acceptable Model ◽  
Conspiracy Beliefs ◽  
Vaccine Confidence ◽  
The Impact

Background: Vaccine hesitancy, associated with medical mistrust, confidence, complacency and knowledge of vaccines, presents an obstacle to the campaign against the coronavirus disease 2019 (COVID-19). The relationship between vaccine hesitancy and conspiracy beliefs may be a key determinant of the success of vaccination campaigns. This study provides a conceptual framework to explain the impact of pathways from conspiracy beliefs to COVID-19 vaccine hesitancy with regard to medical mistrust, confidence, complacency and knowledge of vaccines. Methods: A non-probability study was conducted with 1015 respondents between 17 April and 28 May 2021. Conspiracy beliefs were measured using the coronavirus conspiracy scale of Coronavirus Explanations, Attitudes, and Narratives Survey (OCEANS), and vaccine conspiracy beliefs scale. Medical mistrust was measured using the Oxford trust in doctors and developers questionnaire, and attitudes to doctors and medicine scale. Vaccine confidence and complacency were measured using the Oxford COVID-19 vaccine confidence and complacency scale. Knowledge of vaccines was measured using the vaccination knowledge scale. Vaccine hesitancy was measured using the Oxford COVID-19 vaccine hesitancy scale. Confirmatory factor analysis (CFA) was used to evaluate the measurement models for conspiracy beliefs, medical mistrust, confidence, complacency, and knowledge of vaccines and vaccine hesitancy. The structural equation modeling (SEM) approach was used to analyze the direct and indirect pathways from conspiracy beliefs to vaccine hesitancy. Results: Of the 894 (88.1%) respondents who were willing to take the COVID-19 vaccine without any hesitancy, the model fit with the CFA models for conspiracy beliefs, medical mistrust, confidence, complacency and knowledge of vaccines, and vaccine hesitancy was deemed acceptable. Conspiracy beliefs had significant direct (β = 0.294), indirect (β = 0.423) and total (β = 0.717) effects on vaccine hesitancy; 41.0% of the total effect was direct, and 59.0% was indirect. Conspiracy beliefs significantly predicted vaccine hesitancy by medical mistrust (β = 0.210), confidence and complacency (β = 0.095), knowledge (β = 0.079) of vaccines, explaining 29.3, 11.0, and 13.2% of the total effects, respectively. Conspiracy beliefs significantly predicted vaccine hesitancy through the sequential mediation of knowledge of vaccines and medical mistrust (β = 0.016), explaining 2.2% of the total effects. Conspiracy beliefs significantly predicted vaccine hesitancy through the sequential mediation of confidence and complacency, and knowledge of vaccines (β = 0.023), explaining 3.2% of the total effects. The SEM approach indicated an acceptable model fit (χ2/df = 2.464, RMSEA = 0.038, SRMR = 0.050, CFI = 0.930, IFI = 0.930). Conclusions: The sample in this study showed lower vaccine hesitancy, and this study identified pathways from conspiracy beliefs to COVID-19 vaccine hesitancy in China. Conspiracy beliefs had direct and indirect effects on vaccine hesitancy, and the indirect association was determined through medical mistrust, confidence, complacency, and knowledge of vaccines. In addition, both direct and indirect pathways from conspiracy beliefs to vaccine hesitancy were identified as intervention targets to reduce COVID–19 vaccine hesitancy.

A Cautionary Note on Incremental Fit Indices Reported by LISREL

Methodology ◽  
2005 ◽  
Vol 1 (2) ◽  
pp. 81-85 ◽  
Author(s):  
Stefan C. Schmukle ◽  
Jochen Hardt
Keyword(s):  
Factor Analysis ◽  
Maximum Likelihood ◽  
Structural Equation ◽  
Structural Equation Models ◽  
Null Model ◽  
Likelihood Estimation ◽  
Parameter Estimates ◽  
Fit Indices ◽  
Cautionary Note ◽  
Confirmatory Factor

Abstract. Incremental fit indices (IFIs) are regularly used when assessing the fit of structural equation models. IFIs are based on the comparison of the fit of a target model with that of a null model. For maximum-likelihood estimation, IFIs are usually computed by using the χ2 statistics of the maximum-likelihood fitting function (ML-χ2). However, LISREL recently changed the computation of IFIs. Since version 8.52, IFIs reported by LISREL are based on the χ2 statistics of the reweighted least squares fitting function (RLS-χ2). Although both functions lead to the same maximum-likelihood parameter estimates, the two χ2 statistics reach different values. Because these differences are especially large for null models, IFIs are affected in particular. Consequently, RLS-χ2 based IFIs in combination with conventional cut-off values explored for ML-χ2 based IFIs may lead to a wrong acceptance of models. We demonstrate this point by a confirmatory factor analysis in a sample of 2449 subjects.

Forced Zero Cross-Loading Misspecifications in Measurement Component of Structural Equation Models

Methodology ◽  
2014 ◽  
Vol 10 (4) ◽  
pp. 138-152 ◽  
Author(s):  
Hsien-Yuan Hsu ◽  
Susan Troncoso Skidmore ◽  
Yan Li ◽  
Bruce Thompson
Keyword(s):  
Structural Equation ◽  
Structural Model ◽  
Structural Equation Models ◽  
Equation Model ◽  
Model Fit ◽  
Model Specification ◽  
Simulation Design ◽  
Measurement Models ◽  
Fit Statistics ◽  
Path Coefficients

The purpose of the present paper was to evaluate the effect of constraining near-zero parameter cross-loadings to zero in the measurement component of a structural equation model. A Monte Carlo 3 × 5 × 2 simulation design was conducted (i.e., sample sizes of 200, 600, and 1,000; parameter cross-loadings of 0.07, 0.10, 0.13, 0.16, and 0.19 misspecified to be zero; and parameter path coefficients in the structural model of either 0.50 or 0.70). Results indicated that factor pattern coefficients and factor covariances were overestimated in measurement models when near-zero parameter cross-loadings constrained to zero were higher than 0.13 in the population. Moreover, the path coefficients between factors were misestimated when the near-zero parameter cross-loadings constrained to zero were noteworthy. Our results add to the literature detailing the importance of testing individual model specification decisions, and not simply evaluating omnibus model fit statistics.

scholarly journals Structural Equation Models with Unobservable Variables and Measurement Error: Algebra and Statistics

1981 ◽  
Vol 18 (3) ◽  
pp. 382-388 ◽  
Author(s):  
Claes Fornell ◽  
David F. Larcker
Keyword(s):  
Statistical Analysis ◽  
Measurement Error ◽  
Structural Equation ◽  
Goodness Of Fit ◽  
Structural Equation Models ◽  
Structural Equations ◽  
Testing System

Several issues relating to goodness of fit in structural equations are examined. The convergence and differentiation criteria, as applied by Bagozzi, are shown not to stand up under mathematical or statistical analysis. The authors argue that the choice of interpretative statistic must be based on the research objective. They demonstrate that when this is done the Fornell-Larcker testing system is internally consistent and that it conforms to the rules of correspondence for relating data to abstract variables.

scholarly journals Examining the ParticipACTION brand using the brand equity pyramid

2018 ◽  
Vol 8 (4) ◽  
pp. 378-396 ◽  
Author(s):  
Alexander Lithopoulos ◽  
Peter A. Dacin ◽  
Tanya R. Berry ◽  
Guy Faulkner ◽  
Norm O’Reilly ◽  
...  
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Exploratory Factor Analysis ◽  
Brand Equity ◽  
Structural Equation ◽  
Structural Equation Models ◽  
Equation Modeling ◽  
Content Type ◽  
Activity Promotion ◽  
Confirmatory Factor

Purpose The brand equity pyramid is a theory that explains how people develop loyalty and an attachment to a brand. The purpose of this study is to test whether the predictions made by the theory hold when applied to the brand of ParticipACTION, a Canadian non-profit organization that promotes active living. A secondary objective was to test whether this theory predicted intentions to be more physically active. Design/methodology/approach A research agency conducted a cross-sectional, online brand health survey on behalf of ParticipACTION. Exploratory factor analysis and confirmatory factor analysis established the factor structure. Structural equation modeling was used to test the hypothesized model. Findings A nationally representative sample of Canadian adults (N = 1,191) completed the survey. Exploratory factor analysis and confirmatory factor analysis supported a hypothesized five-factor brand equity framework (i.e. brand identity, brand meaning, brand responses, brand resonance and intentions). A series of structural equation models also provided support for the hypothesized relationships between the variables. Practical implications Though preliminary, the results provide a guide for understanding the branding process in the activity-promotion context. The constructs identified as being influential in this process can be targeted by activity-promotion organizations to improve brand strength. A strong organizational brand could augment activity-promotion interventions. A strong brand may also help the organization better compete against other brands promoting messages that are antithetical to their own. Originality/value This is the first study to test the brand equity pyramid using an activity-promotion brand. Results demonstrate that the brand equity pyramid may be useful in this context.

Confirmatory Factor Analysis and Structural Equation Models to dissect the relationship between Gait and Morphology in Campolina horses

2021 ◽  
pp. 104779
Author(s):  
Fernando de Oliveira Bussiman ◽  
Fabyano Fonseca e Silva ◽  
Rachel Santos Bueno Carvalho ◽  
Ricardo Vieira Ventura ◽  
Elisângela Chicaroni Mattos ◽  
...  
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Structural Equation ◽  
Structural Equation Models ◽  
Confirmatory Factor ◽  
The Relationship

Advances in Factor Analysis and Structural Equation Models

1980 ◽  
Vol 17 (1) ◽  
pp. 133 ◽  
Author(s):  
Richard P. Bagozzi ◽  
Karl G. Joreskog ◽  
Dag Sorbom ◽  
Jay Magidson
Keyword(s):  
Factor Analysis ◽  
Structural Equation ◽  
Structural Equation Models

Executive Functions, Episodic Autobiographical Memory, Problem-Solving Capacity, and Depression Proposal for a Structural Equations Model

2019 ◽  
Vol 32 (2) ◽  
pp. 81-89
Author(s):  
Juan C. Meléndez ◽  
Rita Redondo ◽  
Joaquin Escudero ◽  
Encarna Satorres ◽  
Alfonso Pitarque
Keyword(s):  
Problem Solving ◽  
Executive Functions ◽  
Autobiographical Memory ◽  
Structural Equation ◽  
Structural Equation Models ◽  
Depressive Symptomatology ◽  
Mood State ◽  
Structural Equations ◽  
Healthy Elderly ◽  
Structural Equations Model

The executive functions play an important role in storing and recovering autobiographical memories, especially episodic memories. These types of memories provide information about solutions and experiences from the past that can be utilized as examples in the present when seeking solutions to any problem. In addition, a close relationship between depression and the executive functions has been widely recognized. This study aims to elaborate a structural equations model that empirically supports the relationships among the executive functions, episodic autobiographical memory, and the adaptive capacity to solve problems, taking into account the depressed mood state. In all, 32 healthy elderly people, 32 patients with Parkinson disease, 32 with amnestic mild cognitive impairment, and 32 with Alzheimer disease were evaluated. Structural equation models were estimated to test the effects among the constructs. The final model shows adequate fit indexes, thus revealing that an individual’s problem-solving capacity will depend on the capacity to access the episodic autobiographical memory, which in turn will depend on the maintenance of executive functioning. In a parallel way, the mood state, and specifically depression, will play a modulator role because when there is depressive symptomatology, some capacities that depend on executive control can be diminished.

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