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Dear Dr. Yagihashi,
Thank you for your submission to PeerJ.
On the basis of the reviewers' reports, I am pleased to inform you that your manuscript - 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 - has been Accepted for publication. Many Congratulations!
[# PeerJ Staff Note - this decision was reviewed and approved by Jafri Abdullah, a PeerJ Section Editor covering this Section #]
The author addressed all my comments.
No further comments
No further comments
The authors have addressed all comments I raised.
The authors have addressed all comments I raised.
The authors have addressed all comments I raised.
Dear Dr. Yagihashi,
Thank you for your submission to PeerJ. I am happy to inform you that the manuscript- "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" - has been reviewed by two independent reviewers.
Please submit the rebuttal of each comment raised by the reviewers. \
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The manuscript is clearly stated and methods are well explained. Here are some of my comments for the introduction. As the study was based on survey, there will be potential bias in the answers to question contain sensitive behaviors. There are different sampling techniques that could resolve these issues (randomized response technique), which could be mentioned in the introduction.
Warner SL. Randomized response: A survey technique for eliminating evasive answer bias. Journal of
the American Statistical Association. 1965; 60(309):63–69
Greenberg BG, Kuebler RR Jr, Abernathy JR, Horvitz DG. Application of the randomized response
technique in obtaining quantitative data. Journal of the American Statistical Association. 1971; 66
(334):243–250
Lensvelt-Mulders GJ, Hox JJ, Van der Heijden PG, Maas CJ. Meta-analysis of randomized response
research: Thirty-five years of validation. Sociological Methods & Research. 2005; 33(3):319–348
Cao, M., Breidt, F.J., Solomon, J.N., Conteh, A. and Gavin, M.C., 2018. Understanding the drivers of sensitive behavior using Poisson regression from quantitative randomized response technique data. PloS one, 13(9), p.e0204433.
As above, the sensitivity behavior question and potential selection bias should be discussed. Also, the author may want to discuss the advantages of the longitudinal study.
The method section needs more detail. I suggest that you add more justification on the clustering methods, such as how to choose number of clusters, how to justify the robustness of the cluster choices. Also, with different initial points, even the same clustering method could result different clustering identification. The author may think about different initialization strategies such as kmeans++, random partition, etc.
Thanks for inviting me to review this paper. Overall, exploring clusters of health literacy and beliefs as well as their association with infection prevention behaviors is novel and of great importance. The study design of using prospective study design with large samples is robust. Research questions were clearly defined, and appropriate statistical methods were used.
Several major comments on the method warrant the authors' attention.
1.Sampling distribution of cross marketing needs further elaboration. Previous evidence on the validity and representativeness of cross marketing samples needs to be reviewed and discussed.
2.Sample size should be justified, purely stated that “because of budget limitation” (line 121) is not enough.
3.Health belief model (line 146) etc., may be put into the introduction to consolidate theoretical framework of the present study.
4.Detailed elaboration on manipulation check (lines 122-123) is encouraged.
5.It seems that self-developed items were used based on expert panel discussion (e.g., lines 160-161, lines 181-183). Then professional background of each expert (KH and other co-authors) should be provided, and expert rating to each item should also be supplemented. How did you determine data saturation? This part is very vague, which made content validity questionable.
6.More detailed description of each measurement is encouraged. For example, higher score reflecting xxx; whether some items need reverse scoring.
7.Items generated to measure prevention/risk-taking behaviors were NOT reflecting the ACUTAL BEHAVIORS. They more reflected bias and fear.
Several major comments on the validity of findings warrant the authors' attention.
1.The authors are encouraged to provide demographic summaries of participants (e.g., marital status, income level).
2.Citation(s) need to be provided to support the assumption of correlation among the extracted factors (e.g., "Promax rotation was used for this study because we assumed correlations among the extracted factors”, lines 194-195).
3.Citation(s) need to be provided to support criteria of 0.3 as factor interpretation (e.g., “Factors with high loadings or were considered for factor interpretation”, line 197)
4.The authors said that “We used SPSS (IBM SPSS, Chicago, Illinois, U.S.) version 28.0 for all analyses except the parallel analysis” (line 228-229) - which software was used for parrel analysis? Detailed description on “parallel analysis” is needed here.
5.The authors may consider testing demographic differences between each cluster (e.g., gender, age).
6.Instead of just listing out some sample items of each factor, more elaboration on each factor is encouraged (e.g., lines 263-270; lines 308-317). For the five clusters, the author may consider using figure(s) to visualize features of each cluster.
7.Better to provide percentage of each cluster in the table (e.g., only 3.8% of participants in Cluster 3)
1.Theoretical framework(s) on health literacy and belief should be highlighted in the introduction.
2.The authors should also state more clearly the usefulness of identifying the five clusters, as well as develop the practical implications of the findings.
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