ArticleSafety science2023
Passengers' self-protective intentions while using ride-hailing services during the COVID-19 pandemic.
Article in Safety science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
2 citing papers in PubMed.
- Investigating changes in travel behavior over time in response to the COVID-19 pandemic.Transportation research. Part F, Traffic psychology and behaviour · 2023Article
- Understanding the motivational mechanisms behind the usage frequency of ride-hailing during COVID-19 pandemic.Frontiers in public health · 2022Article
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In the transport context, there has been limited research examining passengers' health-protective behaviour while travelling during a health-related crisis such as COVID-19. This study develops a conceptual model aiming to explore determinants associated with passengers' self-protective intentions using the context of ride-hailing services in Vietnam. Ride-hailing services are popular in countries where public transport is underdeveloped. The conceptual model is based on perceived risk and self-efficacy as the main predictor of self-protective intentions when using ride-hailing services. In addition, the proposed conceptual model explores the direct and indirect impact of subjective knowledge and the perceived effectiveness of preventive measures on self-protective intentions. The proposed conceptual model was tested on a large sample of ride-hailing users in Vietnam (
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.