Utilizing the theory of planned behavior to predict COVID-19 vaccination intention: A structural equational modeling approach

Validating part of the social media infodemic listening conceptual framework using structural equation modelling

“… 11 This research has generally been conducted using surveys and statistical analyses, such as structural equation modelling (SEM), to identify associations. 12 , 13 , 14 , 15 , 16 , 17 SEM has been widely used to investigate factors that influence people's intentions or attitudes towards the COVID-19 vaccination through the use of different theories as well as latent and multiple dependent variables. 12 , 13 , 14 , 15 , 16 , 17 A distinctive feature of SEM is its incorporation of latent variables, which are theoretical constructs that cannot be directly observed or measured but are inferred from a set of measured indicators, such as intentions or perceptions.…”

“… 12 , 13 , 14 , 15 , 16 , 17 SEM has been widely used to investigate factors that influence people's intentions or attitudes towards the COVID-19 vaccination through the use of different theories as well as latent and multiple dependent variables. 12 , 13 , 14 , 15 , 16 , 17 A distinctive feature of SEM is its incorporation of latent variables, which are theoretical constructs that cannot be directly observed or measured but are inferred from a set of measured indicators, such as intentions or perceptions. 12 , 13 , 14 , 15 , 16 , 17 SEM allows researchers to investigate complex relationships among variables, both observable and latent, and offers a practical and flexible tool for understanding complex structural associations.…”

“… 12 , 13 , 14 , 15 , 16 , 17 A distinctive feature of SEM is its incorporation of latent variables, which are theoretical constructs that cannot be directly observed or measured but are inferred from a set of measured indicators, such as intentions or perceptions. 12 , 13 , 14 , 15 , 16 , 17 SEM allows researchers to investigate complex relationships among variables, both observable and latent, and offers a practical and flexible tool for understanding complex structural associations. SEM represents an advanced statistical technique beyond typical regression analysis.…”

“…Unlike regression models, SEM allows multiple dependent variables to be included in the modelling simultaneously. 12 , 13 , 14 , 15 , 16 , 17 This enables researchers to explore not only direct relationships but also indirect relationships, often referred to as paths, among various observable or latent variables. 12 , 13 , 14 , 15 , 16 , 17 Therefore, SEM is particularly well suited for testing multiple hypotheses for various associations within a complex phenomenon.…”

“… 12 , 13 , 14 , 15 , 16 , 17 This enables researchers to explore not only direct relationships but also indirect relationships, often referred to as paths, among various observable or latent variables. 12 , 13 , 14 , 15 , 16 , 17 Therefore, SEM is particularly well suited for testing multiple hypotheses for various associations within a complex phenomenon. For example, several studies have adopted health behavioural theories, such as the health belief model (HBM), theory of planned behaviour (TPB), and extended parallel process model (EPPM), to investigate factors that encourage or discourage COVID-19 vaccine uptake.…”