SciPost Submission Page
Facilitating better sharing quality of COVID-related headlines
by Irene Sophia Plank
Submission summary
| Authors (as registered SciPost users): | Irene Sophia Plank |
| Submission information | |
|---|---|
| Preprint Link: | scipost_202508_00069v2 (pdf) |
| Date submitted: | Oct. 14, 2025, 7:20 p.m. |
| Submitted by: | Irene Sophia Plank |
| Submitted to: | Journal of Robustness Reports |
| Ontological classification | |
|---|---|
| Academic field: | Multidisciplinary |
| Specialties: |
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Abstract
Including accuracy prompts and digital literacy tips similarly decrease the likelihood to share COVID-related headlines, especially if they are false.
Author comments upon resubmission
Dear editor, dear reviewers,
Thank you for the positive and detailed feedback! I detail the changes with respect to the editorial recommendation below in the list of changes. I will also upload responses to each reviewer's individual comments.
Thank you for the positive and detailed feedback! I detail the changes with respect to the editorial recommendation below in the list of changes. I will also upload responses to each reviewer's individual comments.
List of changes
1. I elaborated on the differences and the reason for the re-analysis in the Goal section.
2. I fit a cumulative model with a probit link function to the full, unaggregated data. The model includes random group-level intercepts for persons (slopes for Truth), item (slopes for Condition) and country (slopes for Condition, Truth and their interaction), as suggested by the reviewer. Additionally, I fit an alternative model with Country as a population-level predictor with comparable results.
3. I extended the model to include both interventions of sharing likelihood, i.e., the prompt and the tips condition, explaining the exclusion of the accuracy condition in the manuscript. While I still use sum contrasts, I now also compare the two intervention conditions.
2. I fit a cumulative model with a probit link function to the full, unaggregated data. The model includes random group-level intercepts for persons (slopes for Truth), item (slopes for Condition) and country (slopes for Condition, Truth and their interaction), as suggested by the reviewer. Additionally, I fit an alternative model with Country as a population-level predictor with comparable results.
3. I extended the model to include both interventions of sharing likelihood, i.e., the prompt and the tips condition, explaining the exclusion of the accuracy condition in the manuscript. While I still use sum contrasts, I now also compare the two intervention conditions.
Current status:
In refereeing