Berg Siv Hilde, Lungu Daniel Adrian, Brønnick Kolbjørn, Harthug Stig, Røislien Jo
Centre for Resilience in Healthcare, Faculty of Health Sciences, University of Stavanger, Stavanger, Norway.
Department of Research and Development, Huakeland University Hospital, Bergen, Norway.
JMIR Res Protoc. 2022 Oct 24;11(10):e37441. doi: 10.2196/37441.
Humans struggle to grasp the extent of exponential growth, which is essential to comprehend the spread of an infectious disease. Exponential growth bias is the tendency to linearize exponential functions when assessing them intuitively. Effective public health communication about the nonlinear nature of infectious diseases has strong implications for the public's compliance with strict restrictions. However, there is a lack of synthesized knowledge on the communication of the exponential growth of infectious diseases and on the outcomes of exponential growth bias.
This systematic review identifies, evaluates, and synthesizes the findings of empirical studies on exponential growth bias of infectious diseases.
A systematic review will be conducted using the PRISMA-P (Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols) 2015 statement. Eligibility criteria include empirical studies of exponential growth bias of infectious diseases regardless of methodology. We include studies both with and without interventions/strategies. For information sources, we include the following five bibliographic databases: MEDLINE, Embase, Cochrane Library, PsychINFO, and Web of Science Core Collection. The risk of bias will be assessed using RoB 2 (Risk of Bias 2) and STROBE (Strengthening the Reporting of Observational Studies in Epidemiology). Data synthesis will be achieved through a narrative synthesis.
By February 2022, we included 11 experimental studies and 1 cross-sectional survey study. Preliminary themes identified are the presence of exponential growth bias, the effect of exponential growth bias, and communication strategies to mitigate exponential growth bias. Data extraction, narrative synthesis, and the risk of bias assessment are to be completed by February 2023.
We anticipate that this systematic review will draw some lines related to how people comprehend and misperceive exponential growth and its consequences for infectious disease mitigation and communication. Furthermore, the study will conclude with the limitations of the research and suggestions for future research.
INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/37441.
人类难以理解指数增长的程度，而理解指数增长对于掌握传染病的传播至关重要。指数增长偏差是指在直观评估指数函数时将其线性化的倾向。就传染病的非线性本质进行有效的公共卫生沟通，对于公众遵守严格限制措施具有重要意义。然而，目前缺乏关于传染病指数增长的沟通以及指数增长偏差结果的综合知识。
本系统评价旨在识别、评估和综合关于传染病指数增长偏差的实证研究结果。
将使用2015年版PRISMA-P（系统评价与Meta分析方案的首选报告项目）声明进行系统评价。纳入标准包括关于传染病指数增长偏差的实证研究，不限研究方法。我们纳入有干预措施/策略和无干预措施/策略的研究。关于信息来源，我们纳入以下五个文献数据库：医学期刊数据库（MEDLINE）、荷兰医学文摘数据库（Embase）、考科蓝图书馆（Cochrane Library）、心理学文摘数据库（PsychINFO）和科学引文索引核心合集（Web of Science Core Collection）。将使用偏倚风险2（RoB 2，即偏差风险2）和加强流行病学观察性研究报告（STROBE）来评估偏倚风险。将通过叙述性综合进行数据综合。
截至2022年2月，我们纳入了11项实验性研究和1项横断面调查研究。初步确定的主题包括指数增长偏差的存在、指数增长偏差的影响以及减轻指数增长偏差的沟通策略。数据提取、叙述性综合和偏倚风险评估将于2023年2月完成。
我们预计本系统评价将梳理出一些有关人们如何理解和错误认知指数增长及其对传染病缓解和沟通影响的线索。此外，该研究将总结研究的局限性以及对未来研究的建议。
国际注册报告识别号（IRRID）：DERR1-10.2196/37441
