Investigating confirmation bias in transportation: An analysis of perceived health risk on public transit during the pandemic

https://doi.org/10.1016/j.jth.2022.101485Get rights and content

Highlights

  • Confirmation bias on public transit health risk is examined

  • Having transit access was shown to mitigate confirmation bias

  • High-income people are more likely to have confirmation bias

  • Policymakers should develop more effective communications to overcome this bias

  • Transit agencies can use this methodology to evaluate campaigns' perceptions

Abstract

Introduction

Confirmation bias, the tendency to favor information that confirms their existing beliefs, could be one of the mental barriers that prevents individuals from responding to transportation campaigns and implementing politicians' recommendations. However, previous research has not adequately examined this bias and who is more likely to have it. This study proposes a survey-based experiment to investigate people's confirmation bias on transportation-related topics. The health risks of using public transit during the pandemic were used as an application to examine if confirmation bias exists.

Methods

A survey was designed to investigate the existence of three types of confirmation bias in information search, interpretation, and recall on the topic of health risks of using public transit during the COVID-19 pandemic. Moderation analysis was employed to investigate the impact of individual attributes on the confirmation bias.

Results

The findings support the hypothesis that confirmation bias exists on the topic of public transit health risks. Furthermore, having access to public transit is likely to lessen confirmation bias, while high income and a lack of transit experience are likely to strengthen the confirmation bias. Those who are older, have less experience with public transit, have a higher income, lower education level, and those who identify with a right-leaning political party are less likely to search for, trust, and recall viewpoints that support low health risks associated with public transit.

Conclusions

Confirmation bias was discovered in people's perceptions of transportation topics, providing policymakers with insight into how to frame communications with travelers to counteract this bias. With this information, policymakers can more efficiently evaluate how transportation programs are perceived by diverse populations and develop more targeted campaigns to overcome this bias that encourage wider adoption of future transportation policies and programs.

Introduction

Confirmation bias influences people's perception and absorption of external information, which can influence people's susceptibility to transportation programs such as those that promote sustainability and safety. Confirmation bias is the tendency to favor information that confirms their existing beliefs or hypotheses to decrease cognitive dissonance when people receive and process the external information (Sheela and Mannering, 2020). The term cognitive dissonance is used to describe the mental discomfort that results from holding two conflicting beliefs, values, or attitudes. People tend to seek consistency in their attitudes and perceptions, as reconciling new contradictory information requires mental energy. As a result, they can be less susceptible to the information that contradicts their existing belief.

In particular, confirmation bias could be one of the major factors that prevent people from making sustainable transportation choices, even if they are safer and/or better than less sustainable modes. An example of this would be if confirmation bias prevents people from using public transit following the pandemic. Due to the COVID-19 pandemic, people are reluctant to use public transit due to concerns about disease transmission, which lead to a considerable decline in the number of transit riders (Medlock et al., 2021; Parker et al., 2021). According to data obtained from public transit agencies in April 2020, ridership levels across all public transit modes in the United States have plummeted by 73% (Transitapp, 2022). However, even as more people have been vaccinated and life has returned to some degree of normalcy, transit usage in most US cities has been slow to recover (Quiroz-Gitierrez, 2021; Shapiro, 2022). According to data collected by the American Public Transit Association in April 2022, demand for transit in the United States is still just 62% of what it was pre-pandemic (Saha et al., 2021). Because of the information such as news or other people's opinions that discouraged the use of public transit at the outset of the pandemic, people are still prone to relate public transit to a high risk of disease transmission (Chen, 2020; Kloss, 2020). People may be more likely to only receive transit-related information that supports their beliefs once they have established the opinion that public transit is linked to disease transmission. Confirmation bias, according to research, can lead to people refusing to accept belief-inconsistent public health information, such as vaccine efficacy, thus reinforcing existing preconceptions. (Meppelink et al., 2019; Xu et al., 2022). In the case of this study, confirmation bias could make it difficult for people to return to public transit in the future, affecting public transit operations and reducing long-term funding sources. Furthermore, this bias might lead to more people switching to private vehicles, which will have an adverse consequence for sustainability in the long term. As a result, determining if confirmation bias occurs in the health risk perception associated with public transit is critical. These findings can help transportation agencies build more effective transit campaigns to overcome this bias, which is critical for a broader adoption of more sustainable modes of transportation.

While studies have examined a variety of decision-making biases in people's perception of transportation topics, the existence of confirmation bias and how the bias is moderated by individual attributes have not been adequately evaluated in past literature (Whillans et al., 2020). To this end, several research questions are raised accordingly:

  • Does confirmation bias exist in people's perceptions of transportation-related topics?

  • When are people more prone to experience confirmation bias (e.g., when searching for information, interpreting it, or recalling it)?

  • Is there a link between individual characteristics and confirmation bias when searching for, interpreting, and recalling information?

This study aims to answer the research questions by investigating three types of confirmation bias and how they affect people's perceptions of the health risks of using public transit as an application: confirmation bias in information search, interpretation, and recall, which reflects the situations in which people are most likely to exhibit this bias (Jones and Sugden, 2001). To elicit people's confirmation bias, an innovative and efficient survey-based experiment was used, and moderating analysis was used to investigate the relationship between individual attributes and confirmation bias. The analysis and study application were centered on the topic of the perceived health risk of using public transit during the pandemic. Additionally, to demonstrate the existence of this bias among diverse transportation topics, an analysis of the confirmation bias on a road safety-related topic was performed. The findings of this study contribute to the future evaluation of the responses and effectiveness of transportation policies and programs as well as the development of more targeted campaigns to help people overcome this bias.

This paper is organized into six sections. The following section discusses the literature on confirmation bias and its investigation in transportation. The data collection efforts and analysis methods used in this research are described next. The study results are then presented. Following, the results of this research are discussed. The paper concludes with a study overview with primary research results, policy implications, and limitations.

Section snippets

Post-pandemic transit use

Many researchers have examined how people's behavior changed throughout the pandemic, including changes in activity, mode of transportation, and commuting habits. (Eliasson, 2022). Some research has investigated how these changes have altered travel preferences and habits in ways that may last after the pandemic is over. (Mashrur et al., 2022). According to one estimate, there might be a roughly 40% drop in transit commute trips post-pandemic compared to pre-pandemic, owing to a net shift among

Experiment

Surveys have been extensively used to measure confirmation bias as a simple yet effective method. In order to prevent self-report bias and obtain a more accurate assessment, rather than asking participants to report their own experiences with confirmation bias, an implicit way of experiment was widely applied without the participants understanding the true purpose of the survey. In surveys, respondents are usually asked a question about their original beliefs on the investigated topic before

Results

The significant variables of the information search score, information interpretation score, correct information recall score, and incorrect information recall score identified from the moderation analysis are shown in Table s 2 and .3, and Table .4. Regression diagnostics of the four models were carried out, and errors were found to be normally distributed and homoscedastic.

Table .2 shows the significant variables associated with the information search score. The findings indicate that the

Confirmation bias on a safety topic

While confirmation bias has been found in people's perceptions of the health risk in public transit, a further question is whether confirmation bias can be common for other transportation attitudes; for example, toward a topic that is more permanent than the health risk during the COVID-19/coronavirus pandemic. To answer this question, additional tasks were posed in this survey experiment to see if confirmation bias exists on a different topic, which was selected as to whether decreasing speed

Funding statement

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Author contributions

Melrose Meiyu Pan: Conceptualization, Data Curation, Methodology, Formal Analysis, Writing- Original Draft Preparation, Writing- Reviewing and Editing, Alyssa Ryan: Conceptualization, Methodology, Writing- Reviewing and Editing.

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