Balakrishnan Vimala, Ahhmed Umayma, Basheer Faris
Faculty of Computer Science and Information Technology, Universiti Malaya, Kuala Lumpur, Malaysia.
PLoS One. 2025 Jan 29;20(1):e0317232. doi: 10.1371/journal.pone.0317232. eCollection 2025.
Online malicious attempts such as scamming continue to proliferate across the globe, aided by the ubiquitous nature of technology that makes it increasingly easy to dupe individuals. This study aimed to identify the predictors for online fraud victimization focusing on Personal, Environment and Behavior (PEB).
Social Cognitive Theory (SCT) was used as a guide in developing the PEB framework. Specifically, three factors were identified-Self-awareness (Personal), Attitude (Personal and Environment) and Safe Practice (Behavior) as the potential predictors for online fraud victimization. A self-reporting questionnaire was developed based on the PEB framework and used to collect data targeting Malaysian adults. The study reports result from two separate datasets collected across two separate timelines. Study I involved data collection in January 2023 (n = 820) whereas Study II was conducted with a modified questionnaire from November 2023 -January 2024 (n = 629). Study I identified the online fraud victimization predictors through an Exploratory Factor Analysis (EFA) and a hierarchical binary logistic regression. The dataset from Study II was used to validate the online fraud victimization model derived from Study I by executing another round of hierarchical binary logistic regression.
Results from both the samples show that most of the respondents are aware of digital privacy. EFA from Study I yielded a five-factor solution with a total variance of 60.6%, namely, Self-awareness, Safe Practice, Bank Trust, Overconfidence and Social Influence. Hierarchical binary logistic regression results from both the studies were found to be consistent. Specifically, Overconfidence (β = 0.374; OR = 1.453; 95% CI [1.119, 1.887]; p = 0.005) and Social Influence (β = 0.332; OR = 1.225; 95% CI [1.077, 1.512]; p = 0.006) were found to significantly predict online fraud victimization as well as gender (β = 0.364; OR = 1.440; 95% CI [1.008, 2.016]; p = 0.045) with females exhibiting higher risks to victimization.
The emergence of Overconfidence and Social Influence as significant predictors can guide the development of targeted online fraud awareness campaigns and/or tools emphasizing critical thinking and skepticism. Policymakers can leverage this knowledge to implement regulations that reduce deceptive practices online, promote digital literacy programs, and mandate clearer consumer protections to mitigate the impact of social manipulation and overconfidence on fraud victimization.
This study identifies online fraud victimization predictors, hence improving our understanding of the factors behind this phenomenon-allowing for the development of effective preventive measures and policies to safeguard individuals and improve digital security. For instance, gender- specific educational campaigns can be developed to enhance awareness and equip women with strategies to detect and avoid scams. Additionally, addressing systemic factors like social norms and digital literacy gaps is crucial for creating equitable and effective solutions to reduce online fraud victimization.
诸如诈骗之类的在线恶意行为在全球范围内持续激增，技术的普及使得欺骗个人变得越来越容易，这助长了此类行为的泛滥。本研究旨在确定聚焦于个人、环境和行为（PEB）的在线欺诈受害情况的预测因素。
社会认知理论（SCT）被用作构建PEB框架的指导。具体而言，确定了三个因素——自我意识（个人）、态度（个人和环境）和安全实践（行为）作为在线欺诈受害情况的潜在预测因素。基于PEB框架开发了一份自我报告问卷，并用于收集针对马来西亚成年人的数据。该研究报告了在两个不同时间线收集的两个独立数据集的结果。研究一涉及2023年1月的数据收集（n = 820），而研究二则使用2023年11月至2024年1月修改后的问卷进行（n = 629）。研究一通过探索性因素分析（EFA）和分层二元逻辑回归确定在线欺诈受害情况的预测因素。研究二的数据集用于通过执行另一轮分层二元逻辑回归来验证从研究一得出的在线欺诈受害情况模型。
两个样本的结果均表明，大多数受访者了解数字隐私。研究一的EFA得出了一个五因素解决方案，总方差为60.6%，即自我意识、安全实践、银行信任、过度自信和社会影响。两项研究的分层二元逻辑回归结果一致。具体而言，发现过度自信（β = 0.374；OR = 1.453；95% CI [1.119, 1.887]；p = 0.005）和社会影响（β = 0.332；OR = 1.225；95% CI [1.077, 1.512]；p = 0.006）以及性别（β = 0.364；OR = 1.440；95% CI [1.008, 2.016]；p = 0.045）能显著预测在线欺诈受害情况，女性受害风险更高。
过度自信和社会影响作为重要预测因素的出现，可以指导开展有针对性的在线欺诈意识宣传活动和/或工具的开发，强调批判性思维和怀疑态度。政策制定者可以利用这些知识实施法规，减少在线欺骗行为，推广数字素养计划，并强制实施更明确的消费者保护措施，以减轻社会操纵和过度自信对欺诈受害情况的影响。
本研究确定了在线欺诈受害情况的预测因素，从而增进了我们对这一现象背后因素的理解，有助于制定有效的预防措施和政策来保护个人并改善数字安全。例如，可以开展针对性别的教育活动，提高意识并为女性提供检测和避免诈骗的策略。此外，解决社会规范和数字素养差距等系统性因素对于创建公平有效的解决方案以减少在线欺诈受害情况至关重要。
