Data Archiving Permissions

Transparent data practices that protect participants and support reproducibility.

Journal of Depression and Therapy supports transparent data practices that enable verification and reuse while protecting participant privacy. Authors should plan data sharing early and include clear data availability statements.

Data archiving improves reproducibility, strengthens peer review, and increases the impact of mental health research.

• Select a trusted repository for datasets or instruments
• Provide accession numbers or DOI links in the manuscript
• Include a data dictionary and variable definitions
• Document preprocessing and quality control steps
• Describe software required to open files
• State whether data are open, restricted, or available on request
• De-identify patient information and follow consent terms
• Specify licensing or reuse permissions
• Link related datasets from multi-site studies
• Provide contact details for data queries

Depression research often includes sensitive clinical data. Authors must follow institutional review board guidance, protect participant privacy, and describe any access restrictions clearly.

• Use de-identification or anonymization before sharing
• Describe controlled access procedures for restricted data
• Provide consent language for secondary use
• Explain how data sharing aligns with legal or ethical requirements

If you need help selecting repositories or drafting statements, contact [email protected] for guidance.

Transparent data practices support reproducibility and patient trust.

• Choose a trusted repository for clinical datasets
• Provide dataset DOI or accession number
• Include a data dictionary and variable labels
• Document preprocessing and scoring methods
• Describe file formats and software requirements
• List access restrictions for sensitive data
• Explain de-identification procedures
• Provide consent language for data reuse
• Share analysis code or scripts where possible
• State data retention timelines and governance
• Identify contact details for data access
• Clarify linkage across multi-site datasets
• Describe quality control and validation checks
• Include metadata for instruments or surveys
• Note any licensing terms for data reuse
• Explain how missing data are handled
• Provide versioning information for datasets
• Describe secure storage practices
• List repositories for qualitative data if applicable
• Report updates for longitudinal datasets

Complete documentation reduces data access questions.

• Provide metadata for survey instruments
• Include codebooks for questionnaire data
• Document scoring algorithms
• Describe privacy safeguards for data sharing
• Provide data access request steps
• Note any embargo or restricted timelines
• Include file naming conventions
• Report data versioning details
• List approved data users if restricted
• Describe data backup and retention

Complete, well structured submissions move through review more efficiently and reduce follow up questions.

Data access planning improves transparency while protecting participant privacy.

• Clarify access conditions for sensitive datasets
• Identify data access request contacts
• Document timeframes for data release
• Provide documentation for restricted access
• Include metadata for assessment instruments
• Describe data storage and backup practices
• List software required to use the data
• Report any embargo timelines
• Provide data use agreements if required
• Summarize data governance responsibilities

These small checks help keep manuscripts and communications consistent.

• Keep terminology consistent across sections
• Confirm that tables match reported results
• Use clear headings that guide reviewers
• Provide concise summaries of key findings
• Check that ethics statements are visible
• Align figures with outcome descriptions
• Include clinical implications in discussion
• Verify that all links are current

Quality checks reduce revision cycles and accelerate review.

• Use plain language for complex findings
• Avoid unnecessary jargon or acronyms
• Ensure methods are described in sequence
• Clarify participant flow and attrition
• Report baseline characteristics clearly
• State limitations and generalizability
• Include acknowledgments where needed
• Double check citation formatting