Correlates of COVID-19 conspiracy theory beliefs in Japan: A cross-sectional study of 28,175 residents

Yukihiro Sato; Ichiro Kawachi; Yasuaki Saijo; Eiji Yoshioka; Ken Osaka; Takahiro Tabuchi

doi:10.1371/journal.pone.0310673

Peer Review History

Original SubmissionSeptember 4, 2024
20 Oct 2024 Decision Letter - Osmond Ekwebelem, Editor PONE-D-24-38558 Correlates of COVID-19 conspiracy theory beliefs in Japan: A nationally-representative cross-sectional survey PLOS ONE Dear Dr. Sato, Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process. Please submit your revised manuscript by Dec 04 2024 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file. 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We note that there is identifying data in the Supporting Information file < 2_Suppl.pdf>. Due to the inclusion of these potentially identifying data, we have removed this file from your file inventory. Prior to sharing human research participant data, authors should consult with an ethics committee to ensure data are shared in accordance with participant consent and all applicable local laws. Data sharing should never compromise participant privacy. It is therefore not appropriate to publicly share personally identifiable data on human research participants. The following are examples of data that should not be shared: -Name, initials, physical address -Ages more specific than whole numbers -Internet protocol (IP) address -Specific dates (birth dates, death dates, examination dates, etc.) -Contact information such as phone number or email address -Location data -ID numbers that seem specific (long numbers, include initials, titled “Hospital ID”) rather than random (small numbers in numerical order) Data that are not directly identifying may also be inappropriate to share, as in combination they can become identifying. For example, data collected from a small group of participants, vulnerable populations, or private groups should not be shared if they involve indirect identifiers (such as sex, ethnicity, location, etc.) that may risk the identification of study participants. 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Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: No Reviewer #2: Yes Reviewer #3: Partly Reviewer #4: Yes ******** 2. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: N/A Reviewer #2: Yes Reviewer #3: Yes Reviewer #4: Yes ****** 3. Have the authors made all data underlying the findings in their manuscript fully available? The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified. Reviewer #1: No Reviewer #2: Yes Reviewer #3: No Reviewer #4: No ****** 4. Is the manuscript presented in an intelligible fashion and written in standard English? PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #1: No Reviewer #2: Yes Reviewer #3: Yes Reviewer #4: Yes ****** 5. Review Comments to the Author Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #1: I understand they have many results, but understanding can be challenging. This article should be shorter and easier to understand. I have the following comments: 1- Language: Better language (letter errors, grammar... etc.) is needed. It must use the Grammarly program to become a better manuscript. 2. Methodology: There are a lot of references. It must reduce references in the methodology 2- The result is a lot of mixing and results found in this manuscript. Most of the data is old, as shown: There are very long tables, and many tables are also in the appendix. It isn't easy to understand these tables. Discussion: There is no new result to discuss. Most of these results have been published previously. I can't see new results, and this data is old in use. Therefore, based on the issues identified, the manuscript is not currently suitable for publication in this journal. Significant revisions are necessary to address the concerns raised. It's crucial to condense the results (tables) and enhance the explanation in the discussion and methodology. These improvements are necessary for the manuscript to be considered for publication. Reviewer #2: Dear Authors and Research Team, Your team conducted a social science study on the formation and spread of rumors during the COVID-19 pandemic. This research definitely has important social application value, and I believe it should be published. However, I still have some questions and suggestions for further consideration and revision. Major Opinions 1. In the methods section, the "Study Design, Data Sources, and Participants" discusses the survey questionnaire design. Although you have excluded participants who provided fraudulent responses, I would like to know how your questionnaire distinguishes and confirms the nationality of respondents. 2. This survey was launched on September 27, 2021, and concluded on October 29, 2021. You discuss trust in authorities; however, until October 4, 2021, the authorities were part of the Yoshihide Suga Cabinet, and after that, they belonged to the first Kishida Fumio Cabinet. When designing the survey, did you specify which authorities the participants should consider? If not, I think a more detailed analysis is necessary, as this is very important for the credibility of certain perspectives in the results and discussion. Minor Opinions 1. On page 15, the statement "A broader range of conspiracy theories needs to be considered, including conspiracy theories about vaccines" is ambiguous, making it difficult to understand the authors' specific position and the measures they believe should be taken. The authors should improve the clarity of this expression. 2. In Table 3, the values and headers labeled "B" and "95 CI" are not aligned. These are my suggestions. Good luck with your revisions! Reviewer #3: The introduction sounds quite fragmented. A more cohesive, discursive paragraph is recommended. Conspiracy believes appeared to have recorded even 42,2%. Add findings from Who Believes in COVID-19 Conspiracy Theories in Croatia? Prevalence and Predictors of Conspiracy Beliefs. Tonković M, Dumančić F, Jelić M, Čorkalo Biruški D. Front Psychol. 2021 Jun 18;12:643568. doi: 10.3389/fpsyg.2021.643568. eCollection 2021. Update in light of the recent publications: Factors associated with COVID-19 booster vaccine hesitancy: a nationwide, cross-sectional survey in Japan. Takamatsu A, Honda H, Miwa T, Tabuchi T, Taniguchi K, Shibuya K, Tokuda Y. Public Health. 2023 Oct;223:72-79. doi: 10.1016/j.puhe.2023.07.022. Epub 2023 Aug 22. PMID: 37619504 Effects of Health Literacy in the Fight Against the COVID-19 Infodemic: The Case of Japan. Cheng JW, Nishikawa M. Health Commun. 2022 Nov;37(12):1520-1533. doi: 10.1080/10410236.2022.2065745. Epub 2022 May 3. PMID: 35505456 A quantitative content analysis of topical characteristics of the online COVID-19 infodemic in the United States and Japan. Seah M, Iwakuma M. BMC Public Health. 2024 Sep 9;24(1):2447. doi: 10.1186/s12889-024-19813-y. PMID: 39251957 Free PMC article. Exploratory study to characterise the individual types of health literacy and beliefs and their associations with infection prevention behaviours amid the COVID-19 pandemic in Japan: a longitudinal study. Yagihashi M, Murakami M, Kato M, Yamamura A, Miura A, Hirai K. PeerJ. 2024 Feb 22;12:e16905. doi: 10.7717/peerj.16905. eCollection 2024. PMID: 38406277 Methods The methodology is well-detailed, and the tools are clearly explained, making the study replicable. Although the survey involved a significant sample size of 31,000, the article does not specify whether its characteristics were representative of the general population in Japan. Given the correlation with demographic data, the adoption of stratified sampling would have been advisable. Additionally, the article does not specify the distribution of independent variables, which is particularly important, as these could impact the reported prevalence and correlations. In general, the article is difficult to read due to the multiple variables involved and the way results are presented, which makes concusions unclear as well. Additionally, recommendations for future research are missing. Reviewer #4: This manuscript on the associations between COVID-19 conspiracy theory beliefs and sociodemographic factors, trust in government, etc. as well as with covid vaccine hesitancy tackles a relevant and complex issue. Conceptual framework The manuscript, however, does not include a theoretical or conceptual framework, which could significantly strengthen this manuscript. Although not a deal breaker, it would be helpful if the authors could include a conceptual framework, perhaps with antecedents → beliefs → consequences, if not a proper theory. The inclusion of a theory or framework serves as a guiding structure for your research. Without it, the study feels somewhat exploratory or descriptive, and it becomes harder to draw clear conclusions about the mechanisms at play. I recommend revisiting the literature review to see if there’s a theory or framework that aligns with the factors the authors are investigating. Once identified, it could frame the research questions, guide the discussion of the findings in a more structured way, and suggest avenues for future research. Limitations This study relies on a “nationally representative web-based self-administered questionnaire survey.” Yet, most, but certainly not all, Japanese use the Internet and the sample is self-selected. This should be mentioned in the limitations section, including any information the authors could provide regarding who is likely left out of this “nationally representative” sample. Consequences of correlates of COVID-19 conspiracy theory beliefs The brief description of associations between conspiracy theory beliefs and vaccine hesitancy is an important aspect of this study. I encourage the authors to give this more attention in the manuscript, including suggestions regarding future research to explore the consequences of COVID-19 conspiracy theory beliefs in addition to the correlates of such beliefs. Note: Restrictions on data sharing are addressed in the manuscript. ****** 6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy. Reviewer #1: No Reviewer #2: No Reviewer #3: Yes: Sara Giorgi Reviewer #4: No ******** [NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.] While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step. https://doi.org/10.1371/journal.pone.0310673.r001
Revision 1
22 Nov 2024 Author Response RESPONSES TO REVIEWERS’ COMMENTS Journal requirements 1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf REPLY We have modified our manuscript files to adhere to the style requirements of PLOS ONE. 2. In the online submission form you indicate that your data is not available for proprietary reasons and have provided a contact point for accessing this data. Please note that your current contact point is a co-author on this manuscript. According to our Data Policy, the contact point must not be an author on the manuscript and must be an institutional contact, ideally not an individual. Please revise your data statement to a non-author institutional point of contact, such as a data access or ethics committee, and send this to us via return email. Please also include contact information for the third party organization, and please include the full citation of where the data can be found. REPLY We have modified the data statement. Availability of data and material The data from this study are not stored in a public repository due to the inclusion of personally identifiable or sensitive information. In accordance with Japan’s ethical guidelines, the Research Ethics Committee of the Osaka International Cancer Institute imposed restrictions on data sharing. For any inquiries regarding the data, please contact the JACSIS research office (jacsis_jastis_office@ymail.ne.jp). Details on data availability can be found on the JACSIS website (https://jacsis-study.jp/dug/index. html). 3. We note that there is identifying data in the Supporting Information file < 2_Suppl.pdf>. Due to the inclusion of these potentially identifying data, we have removed this file from your file inventory. Prior to sharing human research participant data, authors should consult with an ethics committee to ensure data are shared in accordance with participant consent and all applicable local laws. Data sharing should never compromise participant privacy. It is therefore not appropriate to publicly share personally identifiable data on human research participants. The following are examples of data that should not be shared: -Name, initials, physical address -Ages more specific than whole numbers -Internet protocol (IP) address -Specific dates (birth dates, death dates, examination dates, etc.) -Contact information such as phone number or email address -Location data -ID numbers that seem specific (long numbers, include initials, titled “Hospital ID”) rather than random (small numbers in numerical order) Data that are not directly identifying may also be inappropriate to share, as in combination they can become identifying. For example, data collected from a small group of participants, vulnerable populations, or private groups should not be shared if they involve indirect identifiers (such as sex, ethnicity, location, etc.) that may risk the identification of study participants. Additional guidance on preparing raw data for publication can be found in our Data Policy (https://journals.plos.org/plosone/s/data-availability#loc-human-research-participant-data-and-other-sensitive-data) and in the following article: http://www.bmj.com/content/340/bmj.c181.long. Please remove or anonymize all personal information (Ages more specific than whole numbers), ensure that the data shared are in accordance with participant consent, and re-upload a fully anonymized data set. Please note that spreadsheet columns with personal information must be removed and not hidden as all hidden columns will appear in the published file. REPLY We carefully reviewed the website and paper you provided. These statements address dataset sharing, not tables. Our supplements contain only tables and no information that could identify individuals, even when combining table data. Therefore, our supplements are suitable for publication. Response to Reviewer 1 I understand they have many results, but understanding can be challenging. This article should be shorter and easier to understand. I have the following comments: REPLY Thank you for your valuable feedback and suggestions. Please find below our point-by-point response to your comments and concerns. 1. Language: Better language (letter errors, grammar... etc.) is needed. It must use the Grammarly program to become a better manuscript. REPLY We have revised the manuscript using the Grammarly carefully. 2. Methodology: There are a lot of references. It must reduce references in the methodology REPLY We have removed some less important references in the methodology. 3. The result is a lot of mixing and results found in this manuscript. Most of the data is old, as shown: There are very long tables, and many tables are also in the appendix. It isn't easy to understand these tables. REPLY We've simplified the results and tables to focus on the most relevant findings. In addition, we removed some less important supplement tables. However, full tables (Tables 1, 2, and 3) are available in the supplementary file for context and transparency. (Line 216–274, page 9–14) Table 1 shows basic participant characteristics (full table in STable 4). The median age of respondents was 50, ranging from 16 to 81. The proportion of women was 50.8%. After imputation and weighting, 10.6% (95% confidence interval [CI] 10.1, 11.1) of the participants believed in one COVID-19 conspiracy theory (OCEANS), 6.5% (95%CI 6.1, 6.9) in two, and 7.3% (95%CI 7.0, 7.8) in three. Thus, the prevalence of harboring at least one COVID-19 conspiracy theory was 24.4% (95%CI 23.7, 25.1). The detailed results of the original categories for three questions on COVID-19 conspiracy beliefs are shown in STable 5. On the other hand, participants who believed in at least one conspiracy theory regarding general vaccines (VCBS) constituted 33.6% (detailed results are shown in STable 6). Table 1. Basic characteristics of 28,175 participants Variable Response participants Imputed population Weighted imputed population 　 n=28,175 (%) n=28,175 (%) n=28,175 (%) The number of conspiracy theory beliefs regarding COVID 19 0 21,414 (76.0%) 21,414 (76.0%) 21,297 (75.6%) 1 2,876 (10.2%) 2,876 (10.2%) 2,974 (10.6%) 2 1,830 (6.5%) 1,830 (6.5%) 1,836 (6.5%) 3 2,055 (7.3%) 2,055 (7.3%) 2,068 (7.3%) The number of conspiracy theory beliefs regarding general vaccines 0 18,798 (66.7%) 18,798 (66.7%) 18,712 (66.4%) 1 3,021 (10.7%) 3,021 (10.7%) 3,010 (10.7%) 2 2,022 (7.2%) 2,022 (7.2%) 2,067 (7.3%) 3 1,180 (4.2%) 1,180 (4.2%) 1,203 (4.3%) 4 873 (3.1%) 873 (3.1%) 865 (3.1%) 5 772 (2.7%) 772 (2.7%) 768 (2.7%) 6 741 (2.6%) 741 (2.6%) 779 (2.8%) 7 768 (2.7%) 768 (2.7%) 770 (2.7%) Age (years old) 16–19 573 (2.0%) 573 (2.0%) 949 (3.4%) 20–24 1,829 (6.5%) 1,829 (6.5%) 1,801 (6.4%) 25–29 1,797 (6.4%) 1,797 (6.4%) 1,834 (6.5%) 30–34 1,963 (7.0%) 1,963 (7.0%) 1,885 (6.7%) 35–39 2,186 (7.8%) 2,186 (7.8%) 2,114 (7.5%) 40–44 2,600 (9.2%) 2,600 (9.2%) 2,350 (8.3%) 45–49 2,854 (10.1%) 2,854 (10.1%) 2,798 (9.9%) 50–54 2,529 (9.0%) 2,529 (9.0%) 2,661 (9.4%) 55–59 2,256 (8.0%) 2,256 (8.0%) 2,250 (8.0%) 60–64 2,234 (7.9%) 2,234 (7.9%) 2,125 (7.5%) 65–69 2,648 (9.4%) 2,648 (9.4%) 2,263 (8.0%) 70–74 2,655 (9.4%) 2,655 (9.4%) 2,781 (9.9%) 75–81 2,051 (7.3%) 2,051 (7.3%) 2,362 (8.4%) Sex Men 13,870 (49.2%) 13,870 (49.2%) 13,986 (49.6%) Women 14,305 (50.8%) 14,305 (50.8%) 14,189 (50.4%) Marital status Married 16,969 (60.2%) 16,969 (60.2%) 17,472 (62.0%) Unmarried 8,322 (29.5%) 8,322 (29.5%) 7,918 (28.1%) Widowed 1,001 (3.6%) 1,001 (3.6%) 1,200 (4.3%) Divorced 1,883 (6.7%) 1,883 (6.7%) 1,585 (5.6%) Educational attainment Lower Secondary School 392 (1.4%) 392 (1.4%) 1,960 (7.0%) Upper Secondary School 7,592 (27.1%) 7,638 (27.1%) 12,780 (45.4%) Specialised Training College (Post-Secondary Courses) 3,203 (11.4%) 3,230 (11.5%) 2,775 (9.9%) Junior College and College of Technology 3,045 (10.9%) 3,065 (10.9%) 2,447 (8.7%) University 12,368 (44.2%) 12,440 (44.2%) 7,421 (26.3%) Master’s or doctor’s degree 1,409 (5.0%) 1,410 (5.0%) 791 (2.8%) (Missing) 166 Employment status Regular employee 9,722 (34.5%) 9,722 (34.5%) 9,231 (32.8%) Temporary employee 4,881 (17.3%) 4,881 (17.3%) 4,976 (17.7%) Self-employed 1,732 (6.1%) 1,732 (6.1%) 1,659 (5.9%) Employer 990 (3.5%) 990 (3.5%) 980 (3.5%) Student 1,267 (4.5%) 1,267 (4.5%) 1,387 (4.9%) Unemployed or retired 4,636 (16.5%) 4,636 (16.5%) 4,768 (16.9%) Home maker 4,711 (16.7%) 4,711 (16.7%) 4,938 (17.5%) Others 236 (0.8%) 236 (0.8%) 235 (0.8%) Annual household income 0 to <2 million yen 2,415 (10.9%) 2,575 (9.1%) 3,298 (11.7%) 2 to <4 million yen 5,738 (25.9%) 7,142 (25.3%) 8,298 (29.5%) 4 to <5 million yen 2,868 (13.0%) 3,908 (13.9%) 3,669 (13.0%) 5 to <8 million yen 6,082 (27.5%) 8,530 (30.3%) 7,219 (25.6%) ≥8 million yen 5,024 (22.7%) 6,020 (21.4%) 5,692 (20.2%) (Missing) 6,048 Household financial assets 0 to <1 million yen 3,034 (17.5%) 4,330 (15.4%) 5,144 (18.3%) 1 to <4 million yen 3,779 (21.8%) 6,707 (23.8%) 7,434 (26.4%) 4 to <9 million yen 3,440 (19.9%) 6,594 (23.4%) 6,245 (22.2%) 9 to <20 million yen 3,247 (18.7%) 5,349 (19.0%) 4,931 (17.5%) ≥20 million yen 3,825 (22.1%) 5,195 (18.4%) 4,422 (15.7%) (Missing) 10,850 Household indebtedness None 15,722 (71.5%) 20,145 (71.5%) 19,914 (70.7%) >0 to <2 million yen 1,510 (6.9%) 2,005 (7.1%) 2,236 (7.9%) ≥2 million yen 4,771 (21.7%) 6,025 (21.4%) 6,025 (21.4%) (Missing) 6,172 　　　　　 Full table is in STable 4. Table 2 presents the weighted mean of the number of COVID‑19 conspiracy beliefs (full table in STable 7). University graduates exhibited a higher endorsement of COVID‑19 conspiracy beliefs (0.49), and the highest annual household income group also showed higher conspiracy beliefs (0.52). Paradoxically, participants who distrusted the Japanese government endorsed fewer conspiracy beliefs (0.40) compared to those who trusted the government (0.56). Table 2. Weighted means of the number of COVID-19 conspiracy beliefs after imputation Variable Mean number of conspiracy theory beliefs regarding COVID 19 The number of conspiracy theory beliefs regarding general vaccines 0 0.41 1 0.48 2 0.45 3 0.45 4 0.56 5 0.50 6 0.75 7 1.12 Educational attainment Lower Secondary School 0.39 Upper Secondary School 0.45 Specialised Training College (Post-Secondary Courses) 0.46 Junior College and College of Technology 0.44 University 0.49 Master’s or doctor’s degree 0.42 Employment status Regular employee 0.51 Temporary employee 0.41 Self-employed 0.44 Employer 0.58 Student 0.52 Unemployed or retired 0.45 Home maker 0.38 Others 0.38 Annual household income 0 to <2 million yen 0.44 2 to <4 million yen 0.45 4 to <5 million yen 0.42 5 to <8 million yen 0.44 ≥8 million yen 0.52 Household financial assets 0 to <1 million yen 0.41 1 to <4 million yen 0.48 4 to <9 million yen 0.46 9 to <20 million yen 0.50 ≥20 million yen 0.42 Household indebtedness None 0.45 >0 to <2 million yen 0.47 ≥2 million yen 0.48 Information source for COVID-19: Websites of government agencies Not use 0.48 Use but distrust 0.66 Use and trust 0.41 Information source for COVID-19: Video sharing platforms (e.g. YouTube) Not use 0.43 Use but distrust 0.50 Use and trust 0.65 Information source for COVID-19: LINE Not use 0.43 Use but distrust 0.57 Use and trust 0.56 Information source for COVID-19: Twitter Not use 0.44 Use but distrust 0.48 Use and trust 0.60 Information source for COVID-19: Facebook Not use 0.44 Use but distrust 0.66 Use and trust 0.77 Information source for COVID-19: Instagram Not use 0.44 Use but distrust 0.60 Use and trust 0.74 Information source for COVID-19: Books Not use 0.43 Use but distrust 0.82 Use and trust 0.72 Information source for COVID-19: TV news Not use 0.54 Use but distrust 0.48 Use and trust 0.43 Information source for COVID-19: Tabloid TV shows Not use 0.46 Use but distrust 0.43 Use and trust 0.46 Trust in the government of Japan Distrust 0.40 Trust 0.56 Full table is in STable 7. Table 3 shows the results of multivariable linear regression analysis with sampling weights after imputation (full table in STable 8). Lower secondary education as well as holding a master’s or doctor’s degree were associated with endorsing fewer COVID-19 conspiracy theories compared with upper secondary education (lower secondary education: B -0.089, 95%CI -0.172, -0.006; master’s or doctor’s degree: B -0.066, 95%CI -0.126, -0.006). Temporary employees (B -0.051, 95%CI -0.095, -0.007), self-employed (B -0.102, 95%CI -0.162, -0.042), unemployed or retired (B -0.078, 95%CI -0.131, -0.025), and home makers (B -0.086, 95%CI -0.135, -0.037) held fewer conspiracy theories compared to regular employees. In addition, higher household income and assets were also associated with endorsing more conspiracy theories (annual household income of ≥8 million yen: B 0.069, 95%CI 0.020, 0.117 vs. 4 to <5 million yen; household financial assets of 9 to <20 million yen: B 0.060, 95%CI 0.010, 0.109 vs. 0 to <1 million yen). As for information sources, participants who used and trusted the websites of government agencies had fewer conspiracy beliefs than those who did not use the websites of government (B -0.109, 95%CI -0.139, -0.079). On the other hand, participants who used and trusted video sharing platforms (e.g. YouTube) (B 0.089, 95%CI 0.038, 0.139), LINE (B 0.053, 95%CI 0.009, 0.097), Facebook (B 0.089, 95%CI 0.000, 0.178), and Instagram (B 0.093, 95%CI 0.008, 0.178) endorsed more conspiracy theories than those who did not use them. Participants who trusted the information from books endorsed more conspiracy beliefs than those who did not use books (B 0.136, 95%CI 0.068, 0.204). Participants who trusted TV news endorsed fewer conspiracy theories (B -0.081, 95%CI -0.128, -0.035 vs. not used), while those who trusted tabloid TV shows held more conspiracy theories (B 0.051, 95%CI 0.015, 0.087 vs. not used). Trust in authorities was associated with endorsing COVID-19 conspiracy beliefs. Trust in the government of Japan was associated with holding more conspiracy theories (B 0.175, 95%CI 0.139, 0.211), compared to those who distrusted government. Table 3. Associations between independent variables and the number of COVID-19 conspiracy beliefs 　 Weighted multivariable adjusted model (n=28,175) Variable Beta 95% confidence interval The number of conspiracy theory beliefs regarding general vaccines 0 (reference) — — 1 0.059 0.017, 0.102 2 0.045 -0.004, 0.094 3 0.040 -0.022, 0.103 4 0.178 0.098, 0.258 5 0.128 0.042, 0.215 6 0.401 0.299, 0.503 7 0.718 0.593, 0.843 Educational attainment Upper Secondary School (reference) — — Lower Secondary School -0.089 -0.172, -0.006 Specialised Training College (Post-Secondary Courses) 0.018 -0.026, 0.06 Attachments Attachment Submitted filename: Response to Reviewers.docx https://doi.org/10.1371/journal.pone.0310673.r002
10 Dec 2024 Decision Letter - Osmond Ekwebelem, Editor Correlates of COVID-19 conspiracy theory beliefs in Japan: A cross-sectional study of 28,175 residents PONE-D-24-38558R1 Dear Dr. Sato, We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements. Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication. An invoice will be generated when your article is formally accepted. Please note, if your institution has a publishing partnership with PLOS and your article meets the relevant criteria, all or part of your publication costs will be covered. Please make sure your user information is up-to-date by logging into Editorial Manager at Editorial Manager® and clicking the ‘Update My Information' link at the top of the page. If you have any questions relating to publication charges, please contact our Author Billing department directly at authorbilling@plos.org. If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org. Kind regards, Osmond Ekwebelem Academic Editor PLOS ONE Additional Editor Comments (optional): Reviewers' comments: https://doi.org/10.1371/journal.pone.0310673.r003
Formally Accepted
16 Dec 2024 Acceptance Letter - Osmond Ekwebelem, Editor PONE-D-24-38558R1 PLOS ONE Dear Dr. Sato, I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now being handed over to our production team. At this stage, our production department will prepare your paper for publication. This includes ensuring the following: * All references, tables, and figures are properly cited * All relevant supporting information is included in the manuscript submission, * There are no issues that prevent the paper from being properly typeset If revisions are needed, the production department will contact you directly to resolve them. If no revisions are needed, you will receive an email when the publication date has been set. At this time, we do not offer pre-publication proofs to authors during production of the accepted work. Please keep in mind that we are working through a large volume of accepted articles, so please give us a few weeks to review your paper and let you know the next and final steps. Lastly, if your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org. If we can help with anything else, please email us at customercare@plos.org. Thank you for submitting your work to PLOS ONE and supporting open access. Kind regards, PLOS ONE Editorial Office Staff on behalf of Dr. Osmond Ekwebelem Academic Editor PLOS ONE https://doi.org/10.1371/journal.pone.0310673.r004

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