Cervical cancer research benefits from transparent, reusable datasets that strengthen clinical translation. Data archiving supports reproducibility, secondary analysis, and program evaluation.

We encourage authors to share de identified datasets, analytic code, and protocols whenever possible.

Select repositories that provide stable identifiers, version control, and access governance. Consider domain specific repositories or institutional archives that align with clinical data standards.

Include a clear data availability statement describing what is shared, where it is hosted, and how it can be accessed.

If access is restricted due to privacy or regulatory constraints, explain the reason and provide contact pathways for qualified access.

Clinical data must be de identified and handled in accordance with ethical approvals. Remove direct identifiers and follow institutional data governance requirements.

When full sharing is not possible, provide aggregated datasets, code, or synthetic data that enables analytic transparency.

Provide documentation that enables reuse and interpretation of datasets.

For guidance on data sharing expectations, contact [email protected].

Data sharing strengthens reproducibility and supports secondary analyses that can inform prevention and treatment strategy. Authors should plan data stewardship early, including repository selection and access governance.

De identified datasets should remove direct identifiers and follow institutional privacy protocols. When sharing clinical data, include clear descriptions of consent language and any restrictions on reuse.

Provide detailed data dictionaries, variable definitions, and codebooks so reviewers and readers can interpret datasets accurately. Clear documentation increases the value of shared resources.

If data are stored in controlled access repositories, describe the request process and review criteria for access. Include contact information for data stewards or institutional offices.

Analytic scripts or statistical code should accompany datasets when possible. Sharing code improves transparency and supports reproducible analysis across research teams.

For longitudinal or registry data, describe update schedules, version control, and how corrections will be documented in archived files.

Cervical cancer research benefits from clear reporting of population characteristics, including age distribution, screening history, and vaccination status. This context helps readers interpret generalizability and informs policy decisions.

When describing interventions, explain how they align with clinical guidelines or public health recommendations. Contextualizing findings supports translation into care pathways.

Transparent reporting of funding sources and resource constraints helps readers assess feasibility in different settings. This is critical for global health adoption.

Where possible, include discussion of equity impacts and strategies to reduce disparities in screening or treatment access.

High quality visual summaries and clear tables improve uptake by clinicians and program managers. Provide succinct interpretations for key outputs.

Consider including patient engagement or community involvement approaches when they inform program design or trial recruitment.

Explain how results compare with prior evidence and identify remaining knowledge gaps for future cervical cancer research.

Ensure terminology is consistent and define acronyms on first use to improve clarity for interdisciplinary audiences.

Discuss potential implications for implementation in low and middle income settings where cervical cancer burden remains high.

The editorial office can advise on scope fit and reporting expectations before submission at [email protected].

Journal of Cervical Cancer is dedicated to advancing cervical cancer prevention, diagnosis, and treatment through transparent publishing.

Our editorial office supports authors, reviewers, and readers with clear guidance and responsive communication. Contact [email protected] for scope or workflow questions.