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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.
DERR1-10.2196/37441
The COVID-19 pandemic has unfortunately demonstrated the power of exponential growth and the need to understand why humans struggle to grasp the extent of a spreading infectious disease. Exponential growth bias is defined by Stango and Zinman [
Exponential growth bias has been documented in numerous contexts and populations, using both experimental and observational methods [
Prior epidemiological studies have documented how the spread of infectious diseases, especially in the initial stages, often follows an exponential function [
Effective public health communication of the nonlinear nature of infectious diseases has strong implications for public compliance with restrictions. However, there is little synthesized knowledge on the communication of exponential growth of infectious diseases and the outcomes of the exponential growth bias. This systematic review identifies, evaluates, and synthesizes the findings of empirical studies on the exponential growth bias of infectious diseases. The review questions are:
What are the consequences of exponential growth bias of infectious diseases?
What strategies can mitigate 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 [
Consistent with the aim to identify findings of empirical studies, we include empirical studies regardless of applied methodology (eg, randomized controlled trials, nonrandomized studies [quasi-experimental trials], survey studies, and qualitative studies). Commentaries, reviews, opinion pieces, or other papers not reporting primary empirical research are excluded. Only English-language peer-reviewed studies are included. PICO (Problem, Intervention or Exposure, Comparison, Outcome) is used to define our rationale and eligibility criteria.
We include studies of exponential growth bias of infectious diseases. We define exponential growth bias as “the pervasive tendency to linearize exponential functions when assessing them intuitively” [
We included studies both with and without interventions/strategies to mitigate exponential growth bias.
The studies have to report on the presence of exponential growth bias of infectious diseases to be included. Additional outcomes of interest, which are not necessary to be eligible for inclusion, are the outcomes of strategies to mitigate exponential growth bias of infectious diseases and the outcomes of exponential growth bias of infectious diseases.
A presearch provided a limited number of hits. To increase the sensitivity of the search, we include five bibliographic databases: MEDLINE, Embase, Cochrane Library, PsychINFO, and Web of Science Core Collection. Based on initial literature searches, several papers were selected for further cited reference searches in Web of Science as a supplement to the traditional searches. In line with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines [
As of February 2022, the search yielded 585 results. After removing duplicates, there were 365 unique results. The full text of 50 articles were read and assessed for eligibility; 39 were excluded, and 11 were included in the review.
One reviewer (SHB) undertook the screening and inclusion, in dialogue with author JR. All records were added to Rayyan (software for intelligent systematic review). SHB assessed abstracts and full-text articles using the eligibility criteria.
Data will be extracted by one researcher (SHB) and will be checked by a second researcher (DAL or JR). Data from included papers will be extracted to a matrix prior to synthesis: author, year of publication, aim, sample size, origin, methods, and results. Pilot-testing of the data extraction form has been conducted by extracting information from 3 studies. The extracted data will be displayed in a table, and the content of the table will be validated by JR and DAL.
Due to the heterogeneity of the studies regarding methodology and outcome measures, a statistical meta-analysis was considered inappropriate [
Risk of bias will be assessed using the ROBINS-I (Risk of Bias in Nonrandomized Studies of Interventions), the preferred tool to be used in Cochrane reviews for nonrandomized studies of interventions [
Template for the risk of bias assessment in accordance to ROBINS-I (Risk of Bias in Nonrandomized Studies of Interventions) [
|
Studies |
Confounding | —a |
Selection of participants | — |
Classifications of interventions | — |
Deviations from interventions | — |
Missing data | — |
Measurement of outcome | — |
Selection of reported results | — |
Overall risk of bias | — |
aReference numbers will be included here.
Template for risk of bias assessment in accordance to RoB 2 (Risk of Bias 2) [
|
Studies |
Randomization process | —a |
Deviations from interventions | — |
Missing data | — |
Measurement of outcome | — |
Selection of reported results | — |
Overall risk of bias | — |
aReference numbers will be included here.
As of February 2022, we have included 11 studies (see the PRISMA flow diagram in
PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) flow diagram for studies included in the present review of exponential growth bias (EGB).
This review presents an unbiased summary and analysis of the evidence of the exponential growth bias of infectious diseases. We believe that the review will provide useful information to guide future research and public health communication strategies. The anticipated main findings of this study will document the presence of exponential growth bias of infectious diseases and its personal and societal consequences, and identify communication strategies that may mitigate the exponential growth bias of infectious diseases. However, since this research is in its early development, we expect to find few methodologically diverse studies. Although we cannot conduct a meta-analysis and statistical synthesis of the outcomes in this systematic overview, we expect this review to generate scholarly discussion and research. Thus, the discussion will focus on the limitations of the research and suggestions for future research in the fields of health communication, media studies, psychology, and mathematics. The review is expected to be submitted to the
Search strategy.
Problem, Intervention or Exposure, Comparison, Outcome
Preferred Reporting Items for Systematic Reviews and Meta-Analyses
Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols
Risk of Bias 2
Risk of Bias in Nonrandomized Studies of Interventions
Strengthening the Reporting of Observational Studies in Epidemiology
We thank our funder. The COVID Communication: Fighting a Pandemic Through Translating Science (COVCOM) project has received funding from the Trond Mohn Foundation under grant TMS2020TMT10 and the University of Stavanger. We also thank the university librarian Geir Strandenæs Larsen who assisted in the selection of databases, search terms, and search methodology, and who designed the final search.
SHB had the original idea for the study and designed the work. As of February 2022, SHB screened and extracted data. SH reviewed the search terminology. KB validated the procedure for the risk of bias assessment. JR and DAL validated the search strategy and inclusion of selected studies. All authors contributed substantially to the methodological design of the protocol and approved the final manuscript.
None declared.