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pmid: 40477725
pmc: PMC9486796
AbstractThis study examines the impact of the COVID-19 pandemic and tourist’s assessments of non-pharmaceutical public-health interventions (NPIs) in relation to their travel intentions. It uses a combined theoretical model that incorporates the Domain-Specific Risk-Taking Scale (DOSPERT) in the recreational domain, the Health Belief Model (HBM) and the Theory of Planned Behaviour (TPB). A large-scale population study that is representative of Switzerland has been carried out to validate the model (N = 1683; 39% response rate). We use a regression model based on mean indices for our explanatory model. Health beliefs, namely perceived susceptibility and severity, are important predictors of travel intentions. The perceived benefits of and barriers to compliance with NPIs when travelling also have a substantial influence on travel intentions. The results demonstrated that the factors of the HBM tend to have a stronger influence than other significant factors, such as the perceived behavioural control of the TPB. As a situational context, the ability to work from home increases the intention to travel. The achievement of the present research is a validated empirical theory-based model that is suitable for practical and managerial implications. It can be used to create and evaluate measures and interventions that address the social psychological influencing factors.
Travel intentions, NPIs, Health belief model, Research, Risk-taking behaviour, Theory of planned behaviour, Psychology, COVID-19, BF1-990
Travel intentions, NPIs, Health belief model, Research, Risk-taking behaviour, Theory of planned behaviour, Psychology, COVID-19, BF1-990
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 4 | |
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| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
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