Correcting cognitive biases for safer online behaviors: experimental evidence from migrants across major cities in Vietnam

Our intervention aims to (1) help participants recognize how common thinking shortcuts, known as cognitive biases, can influence their online decisions and increase their exposure to cyber risks, and (2) provide practical tips and strategies to mitigate these risks by encouraging more rational and reflective decision-making.
Phase I:
1. Recognizing personal biases:
Participants first answer short questions designed to reveal two common biases: anchoring bias (being overly influenced by the first piece of information) and availability bias (relying too much on easily remembered events). Afterward, we show them how these biases may have influenced their own answers. This helps raise awareness that everyday judgments and online decisions can be shaped by subtle cues.

2. Learning practical strategies:
Next, participants watch a short, four-minute educational video explaining how to think more critically when consuming and sharing information online. The video provides simple, concrete tips - such as pausing before sharing content, verifying information through trusted sources, and discussing uncertain information with others. The goal is to encourage reflective thinking and safer online behavior.

Participants in the control group watch a neutral video about tips for attending wedding or anniversary parties of the same length, ensuring that only the content (not the format or duration) differs between groups.

Phase II: Follow-up Reminders

To reinforce the treatment message and encourage retention, participants in the treatment group will receive short reminder messages via SMS or Zalo every two weeks. Each message will briefly restate key points from the intervention (e.g., pausing before sharing, verifying information sources) and include a link to rewatch the 4-minute instrumnetal video.

These reminders are designed to maintain awareness of safe online behaviors and strengthen the long-term effect of the bias-correction intervention.

2025-10-06

2025-12-31

In the within-subjects design, the outcome measures focus on changes in participants’ past and intentional behaviors before (baseline survey) and after the intervention (endline survey to be implemented about one month after the intervention). Specifically, before the treatment, we measure participants’ behavior during the previous month related to sharing unverified online content using both direct (self-reported) (Zhang & Cheng, 2024) and indirect (list experiment) methods (Pham et al., 2024).
In the between-subjects design, we compare the treatment and control groups to evaluate the overall effectiveness of the bias-awareness and critical-thinking intervention. To assess the immediate treatment effect, we compare participants’ likelihood of sharing unverified information and their response times when asked about sharing the online treatment content. We also record the time participants take to respond when asked whether they would share the video content used in the treatment. This response time serves as an indicator of cognitive processing depth — faster responses may reflect heuristic thinking, while slower and more deliberate responses suggest greater cognitive reflection following the intervention. In addition, the study includes the Cognitive Reflection Test (Thomson & Oppenheimer, 2016) to examine whether the intervention enhances cognitive reflection, thereby reducing the likelihood of sharing unverified information.

Reference
Pham, T., Goto, D., & Tran, D. (2024). Child online safety education: A program evaluation combining a randomized controlled trial and list experiments in Vietnam. Computers in Human Behavior, 156, 108225.
Thomson, K. S., & Oppenheimer, D. M. (2016). Investigating an alternate form of the cognitive reflection test. Judgment and Decision Making, 11(1), 99–113.
Zhang, Z., & Cheng, Z. (2024). Users’ unverified information-sharing behavior on social media: The role of reasoned and social reactive pathways. Acta Psychologica, 245(October 2023), 104215. https://doi.org/10.1016/j.actpsy.2024.104215

This study employs a randomized controlled experimental design to assess the impact of a behavioral video intervention and follow-up nudges on reducing high-risk online information sharing. Participants were randomly assigned to either a treatment or control group. At baseline, all participants completed measures of high-risk online behavior using both direct self-reports and an indirect list experiment. They were also assessed for cognitive biases, specifically anchoring and availability. Following this, participants viewed a four-minute video tailored to their group: the treatment group watched a video promoting bias awareness and critical thinking strategies, while the control group viewed a placebo video unrelated to online behavior, focusing instead on tips for organizing wedding or anniversary parties.

Immediately after the video, participants in both groups completed attention and understanding checks, a Cognitive Reflection Test (CRT), and responded to outcome measures including the likelihood of sharing verified and unverified information and the timing of their responses to sharing prompts. These assessments aimed to capture both immediate cognitive engagement and behavioral intent following the intervention. Demographic characteristics, internet use frequency, and prior scam exposure were collected as control variables.

In Phase II, only participants in the treatment group received brief behavioral reminder messages every two weeks via SMS or Zalo. These nudges were designed to reinforce the bias-awareness content of the initial video. At the end of the study, an endline survey was administered to both groups to reassess high-risk behavior through the same indirect and direct methods used at baseline, as well as to re-measure information-sharing likelihood and response timing. This design allows for evaluating both the short-term and sustained impacts of the intervention and nudges on participants' online behavior.

Not available

At individual level by the automatic Survey Solution system.

Individual level

No

Approximately 250 migrants are randomly assigned to each treatment arm, resulting in about 500 migrants in total. With two rounds of data collection (baseline and endline), this yields approximately 1,000 observations.

Approximately 250 migrants are randomly assigned to each treatment arm, resulting in about 500 migrants in total. With two rounds of data collection (baseline and endline), this yields approximately 1,000 observations.

Approximately 250 migrants are randomly assigned to each treatment arm, resulting in about 500 migrants in total. With two rounds of data collection (baseline and endline), this yields approximately 1,000 observations.

Given a sample of 250 individuals per group (500 total), measured at baseline and endline, the minimum detectable effect size (MDES) is approximately 0.07–0.09 units, assuming an outcome standard deviation of 0.4–0.5. This corresponds to detecting a change of about 14%–18% of the mean outcome (if mean = 0.5), with 80% power and 5% significance, accounting for repeated measures and modest within-subject correlation.