An examination of the factorial and convergent validity of four measures of conspiracist ideation, with recommendations for researchers.
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ABSTRACT:
SUBMITTER: Swami V
PROVIDER: S-EPMC5322923 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:The purpose of the current investigation is to assess and validate the factor structure of the Behavioral Risk Factor Surveillance System's (BRFSS) Adverse Childhood Experience (ACE) module.ACE data available from the 2009 BRFSS survey were fit using exploratory factor analysis (EFA) to estimate an initial factorial structure. The exploratory solution was then validated using confirmatory factor analysis (CFA) with data from the 2010 BRFSS survey. Lastly, ACE factors were tested for measurement invariance using multiple group factor analysis.EFA results suggested that a 3-factor solution adequately fit the data. Examination of factor loadings and item content suggested the factors represented the following construct areas: Household Dysfunction, Emotional/Physical Abuse, and Sexual Abuse. Subsequent CFA results confirmed the 3-factor solution and provided preliminary support for estimation of an overall latent ACE score summarizing the responses to all available items. Measurement invariance was supported across both gender and age.Results of this study provides support for the use of the current ACE module scoring algorithm, which uses the sum of the number of items endorsed to estimate exposure. However, the results also suggest potential benefits to estimating 3 separate composite scores to estimate the specific effects of exposure to Household Dysfunction, Emotional/Physical Abuse, and Sexual Abuse.
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Project description:BACKGR1OUND: Widespread vaccine hesitancy and refusal complicate containment of the SARS-CoV-2 pandemic. Extant research indicates that biased reasoning and conspiracist ideation discourage vaccination. However, causal pathways from these constructs to vaccine hesitancy and refusal remain underspecified, impeding efforts to intervene and increase vaccine uptake.Method554 participants who denied prior SARS-CoV-2 vaccination completed self-report measures of SARS-CoV-2 vaccine intentions, conspiracist ideation, and constructs from the Health Belief Model of medical decision-making (such as perceived vaccine dangerousness) along with tasks measuring reasoning biases (such as those concerning data gathering behavior). Cutting-edge machine learning algorithms (Greedy Fast Causal Inference) and psychometric network analysis were used to elucidate causal pathways to (and from) vaccine intentions.ResultsResults indicated that a bias toward reduced data gathering during reasoning may cause paranoia, increasing the perceived dangerousness of vaccines and thereby reducing willingness to vaccinate. Existing interventions that target data gathering and paranoia therefore hold promise for encouraging vaccination. Additionally, reduced willingness to vaccinate was identified as a likely cause of belief in conspiracy theories, subverting the common assumption that the opposite causal relation exists. Finally, perceived severity of SARS-CoV-2 infection and perceived vaccine dangerousness (but not effectiveness) were potential direct causes of willingness to vaccinate, providing partial support for the Health Belief Model's applicability to SARS-CoV-2 vaccine decisions.ConclusionsThese insights significantly advance our understanding of the underpinnings of vaccine intentions and should scaffold efforts to prepare more effective interventions on hesitancy for deployment during future pandemics.
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